JP2004097704A - Game machine, game control process, and control program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To make a player thrilled and excited. <P>SOLUTION: The game machine comprises a rating part 380 for rating the second form element information according to the frequency of searching the second form element information including the first form element information based on the result of the search executed by a topic searching part 360, an acquisition part 371 for acquiring the code information coincide with the ranking among code information by collating the ranking rated by the rating part 380 and the code information, and a first winning determining part 2300 for determining the winning state according to the winning probability value corresponding to the code information acquired by the acquisition part 371. <P>COPYRIGHT: (C)2004,JPO

Description

[0001]
TECHNICAL FIELD OF THE INVENTION
The present invention relates to a gaming machine, a game control method, and a control program for determining whether or not a winning state is established when a gaming ball is inserted into a winning opening.
[0002]
[Prior art]
A pachinko gaming machine, which is a type of a conventional gaming machine, determines whether or not to shift to a state in which many gaming balls are discharged when a gaming ball is inserted into a winning opening (winning state). At this time, the pachinko gaming machine determines the winning state according to the predetermined winning probability with reference to the predetermined winning probability table.
[0003]
When the pachinko gaming machine determines to shift to the winning state, the pachinko gaming machine further performs the following determination. That is, the gaming machine determines whether or not to refer to a table with a high winning probability value (determines whether or not to enter a probability variation state). (For example, see Patent Document 1).
[0004]
[Patent Document 1]
JP-A-2000-70489 (P6)
[0005]
[Problems to be solved by the invention]
However, the above-described related art has the following problems. The case where the winning probability changes during the game is the case where it is determined that the gaming machine shifts to the winning state. For this reason, the player tends to think that the winning probability is unlikely to change during the game.
[0006]
As a result, the player thinks that the player will not easily be in a winning state or will not be likely to be in a winning state in the game. Therefore, the player played the game with a lack of thrill and excitement.
[0007]
Here, if there is a gaming machine that can change the winning probability based on the content uttered by the player, the player can play a game with the following feeling.
[0008]
That is, during the game, the gaming machine may be less likely to be in a winning state or may be more likely to be in a winning state depending on the content of the player's speech. As a result, the player can play the game with thrill and excitement.
[0009]
Therefore, the present invention has been made in view of the above points, and it is possible to give a thrill and excitement to a player by changing a winning probability based on the uttered content of the player. It is an object of the present invention to provide a gaming machine, a control method, and a control program that can be used.
[0010]
[Means for Solving the Problems]
The invention according to the present application is directed to a gaming machine having a determination means for determining the winning state when the gaming ball is inserted into a winning opening for receiving a gaming ball for determining a winning state for discharging a predetermined number of gaming balls. When controlling the game, when the game ball is inserted into the winning opening, a winning probability value indicating the probability that the determination means determines the winning state is associated with code information including a numerical value, A plurality of winning probability values are stored in advance in the first storage means, and at least one morpheme constituting the minimum unit of the character string is extracted as first morpheme information based on the character string of the input information input from the player. Then, a plurality of pieces of second morpheme information indicating a predetermined morpheme are stored in advance in the morpheme storage means, and the extracted first morpheme information and the respective second morpheme information are collated, and From the first form Searching for the second morpheme information including the information, based on the retrieved search result, from the respective second morpheme information, the frequency of the frequency at which the second morpheme information including the first morpheme information is searched Based on the ranked rank, based on the ranked rank, the rank and the respective code information are collated, and from among the respective code information, code information that matches the rank is obtained, and the obtained code information is obtained. The determination means determines the winning state according to a winning probability value corresponding to the code information.
[0011]
Further, according to the present invention, in the above invention, when the gaming ball is inserted into the winning opening, the determination means determines that each piece of identification information including each numerical value corresponds to the winning information indicating whether or not the winning state is established. With reference to the attached first table, predetermined identification information is selected from among the pieces of identification information, and the winning state is determined based on the winning information corresponding to the predetermined identification information. The winning probability value calculated based on the number of each piece of identification information and the number of winning identification information that is the identification information associated with the winning information indicating the winning state, and the winning probability value A plurality of the first tables are stored in the first storage unit in advance, and the determination unit refers to the first table corresponding to the acquired code information. Is specified in each identification information Select the identification information, based on the winning information corresponding to the predetermined identification information, it is also possible to determine the winning state.
[0012]
Further, in the above invention, it is preferable that the ranked size is a degree of emotion held by the player. In addition, it is preferable to rank a low rank when the search frequency is low, and rank a high rank when the search frequency is high.
[0013]
Further, according to the present invention, in the above invention, when the determining means determines that the winning state is established, it is determined whether or not the ranked current rank is the highest, and each identification information and the winning information are determined. The winning probability value calculated based on the number of each piece of the identification information in the second table and the number of the winning identification information in the second table is associated with each first table. When the second rank is higher than the highest winning probability value among the assigned winning probability values and the second table is stored in advance in the second storage means, and the current rank is determined to be the highest, the determining means May refer to the second table, select predetermined identification information among the pieces of identification information, and determine the winning state based on the winning information corresponding to the predetermined identification information.
[0014]
BEST MODE FOR CARRYING OUT THE INVENTION
[First embodiment]
(Basic configuration of conversation control system)
A conversation control system according to the present invention will be described with reference to the drawings. FIG. 1 is a schematic configuration diagram of a conversation control system having a conversation control device 1 (ranking device) according to the present embodiment.
[0015]
As shown in FIG. 1, the conversation control device 1 includes an input unit 100, a speech recognition unit 200, a conversation control unit 300, a sentence analysis unit 400, a conversation database 500, an output unit 600, and a speech recognition dictionary storage. And a unit 700.
[0016]
In the present embodiment, for convenience of explanation, the description will be limited to the utterance content of the user (this utterance content is a type of input information). However, the present invention is not limited to the utterance content of the user, and is not limited to the utterance content of the user. For example, the input information may be input from a user or the like. Therefore, the "speech content" described below can also be described by replacing "speech content" with "input information".
[0017]
Similarly, in the following description, for convenience of explanation, the description will be limited to “speech sentence type” (speech type). The “input type” indicating the type of input information that has been input may be used. Therefore, the "utterance sentence type" (utterance type) described below can also be described by replacing "utterance type" with "input type".
[0018]
The input unit 100 is an obtaining unit that obtains input information from a user. In the present embodiment, the input unit 100 includes a microphone, a keyboard, and the like. The input unit 100 is also a character recognition unit that specifies a character string indicating input information based on input information (other than voice) input from a user.
[0019]
Here, the input information means characters, symbols, voices and the like input through a keyboard or the like. Specifically, the input unit 100 specifies a character string indicating the input information based on the input information (other than voice), and outputs the specified character string to the conversation control unit 300 as a character string signal. Also, the input unit 100 that has acquired the utterance content from the user (this utterance content is composed of voice and is a type of input information) with a microphone or the like, the input unit 100 converts the voice constituting the acquired utterance content into an audio signal. Is output to the voice recognition unit 200.
[0020]
The voice recognition unit 200 is a character recognition unit that specifies a character string corresponding to the utterance content based on the utterance content acquired by the input unit 100. Specifically, the speech recognition unit 200 to which the speech signal is input from the input unit 100 analyzes the input speech signal, and stores a character string corresponding to the analyzed speech signal in the speech recognition dictionary storage unit 700. The specified character string is output to the conversation control unit 300 as a character string signal. The voice recognition dictionary storage unit 700 stores a dictionary corresponding to a standard voice signal.
[0021]
The sentence analysis unit 400 analyzes a character string specified by the input unit 100 or the speech recognition unit 200. In the present embodiment, as shown in FIG. 2, a morpheme extraction unit 410 and a phrase analysis unit 420 , A sentence structure analysis unit 430, an utterance type determination unit 440, a morpheme database 450, and an utterance type database 460.
[0022]
The morpheme extraction unit 410 is a morpheme extraction unit that extracts each morpheme constituting the minimum unit of the character string as first morpheme information based on the character string specified by the input unit 100 or the speech recognition unit 200.
[0023]
Specifically, the morpheme extraction unit 410 to which the character string signal is input from the management unit 310 extracts each morpheme from the character string corresponding to the input character string signal. Here, in the present embodiment, a morpheme means a minimum unit of a word configuration represented in a character string. As shown in FIG. 3, examples of the minimum unit of the word configuration include a part of speech such as a noun, an adjective, and a verb. In the present embodiment, each morpheme is represented as m1, m2,..., Ml.
[0024]
That is, the morpheme extraction unit 410 collates a character string corresponding to the input character string signal with a morpheme group such as a noun, adjective, or verb stored in the morpheme database 450 in advance, and extracts a morpheme from the character string. Each morpheme (m1, m2,...) That matches the group is extracted, and each extracted morpheme is output to the phrase analysis unit 420 as an extraction signal.
[0025]
The phrase analysis unit 420 is a conversion unit that converts each morpheme into a phrase format based on each morpheme extracted by the morpheme extraction unit 410. Specifically, the phrase analysis unit 420 to which the extraction signal is input from the morpheme extraction unit 410 uses the respective morphemes corresponding to the input extraction signal to combine them into a phrase format.
[0026]
In the present embodiment, the phrase form refers to a sentence having an independent word or an independent word with one or more attached words in the Japanese grammar, or a character string that does not break the meaning of the Japanese grammar. It means a sentence that is as small as possible. This clause is expressed as p1, p2,... Pk in the present embodiment.
[0027]
That is, as shown in FIG. 4, the phrase analyzing unit 420 converts the dependency element of each morpheme (for example, (m2) · (m4) · (m5) based on each morpheme corresponding to the input extracted signal. ) ..) are extracted, and each morpheme is grouped into each phrase based on the extracted dependency elements. "T" shown in the figure means transposition.
[0028]
The phrase analysis unit 420 that compiles each morpheme into each phrase, the sentence structure analysis unit 430 and the utterance type determination unit 440, using the morphological information including each morpheme that summarizes each morpheme and each morpheme that composes each phras as a morphological signal. Output to
[0029]
The sentence structure analysis unit 430 is a classification unit that classifies each morpheme of the first morpheme information segmented by the phrase analysis unit 420 into attributes such as subject matter and object case. Specifically, the sentence structure analysis unit 430 to which the sentence pattern signal is input from the sentence pattern analysis unit 420, based on each morpheme corresponding to the input sentence pattern signal and the sentence formed by each morpheme, Determine the "case composition".
[0030]
Here, the “case composition” means a case (attribute) indicating a substantial concept in a phrase, and in the present embodiment, for example, a subject (subject case) meaning a subject / subject and an object Examples include a meaningful object (target case), an action meaning an action, a time meaning a time (tense, aspect), a location meaning a place, and the like. In the present embodiment, each morpheme associated with three elements “case” (case configuration) of a subject, an object, and an action is defined as first morpheme information.
[0031]
That is, as shown in FIG. 5, for example, when the dependency element of each morpheme is "" or "ha", the sentence structure analysis unit 430 determines that the morpheme before the dependency element is the subject (subject) Or nominative). Also, the sentence structure analysis unit 430
For example, when the dependency element of each morpheme is "" or "", it is determined that the morpheme in front of the dependency element is an object (object).
[0032]
Further, for example, when the dependency element of each morpheme is “do”, the sentence structure analysis unit 430 determines that the morpheme preceding the dependency element is an action (predicate; this predicate is composed of a verb, an adjective, etc.). Is determined.
[0033]
The sentence structure analysis unit 430 that has determined the “case configuration” of each morpheme constituting each phrase, based on the first morpheme information associated with the determined “case configuration”, determines the range of a topic described below. A topic search command signal for specifying is output to the reflective determination unit 320.
[0034]
The utterance type determination unit 440 is a type specifying unit that specifies an utterance type (input type) indicating the type of utterance content (input information) based on the phrase specified by the phrase analysis unit 420. Specifically, the “speech sentence type” (speech type) is determined based on each morpheme corresponding to the sentence pattern signal input from the phrase analysis unit 420 and the clause composed of each morpheme.
[0035]
In this embodiment, as shown in FIG. 6, the “utterance sentence type” is a statement (D; Declaration), a comment sentence (I; Impression), a conditional sentence (C; Condition), and a result sentence (D: Declaration). E; Effect), time sentence (T; Time), place sentence (L; Location), repulsion sentence (N; Negation), and the like.
[0036]
The statement is a sentence composed of a user's opinion or idea, and in the present embodiment, as shown in FIG. 6, a sentence such as "I like Sato" is exemplified. The impression sentence means a sentence composed of impressions held by the user. The location sentence means a sentence composed of locational elements.
[0037]
The result sentence means a sentence composed of a sentence including a result element for a topic. The time sentence means a sentence including a temporal element related to a topic.
[0038]
The conditional sentence means a sentence including elements such as a premise of the topic and a condition or a reason why the topic is established when one utterance is regarded as a topic. The repulsive sentence means a sentence including an element that repels the utterer. An example sentence for each “utterance sentence type” is as shown in FIG.
[0039]
That is, based on each phrase corresponding to the input sentence pattern signal, the utterance type determination unit 440 collates each phrase with each dictionary stored in the utterance type database 460, and from among each phrase, Extract sentence elements related to the dictionary. The utterance type determination unit 440 that extracts a sentence element related to each dictionary from each phrase determines a “speech sentence type” based on the extracted sentence element. The sentence element means a minute type for specifying the type of the character string, and in the present embodiment, the sentence element includes the above-described definition phrase (to).
[0040]
Here, the utterance type database 460 includes, as shown in FIG. 7, a definition expression example dictionary including a dictionary related to a definition phrase (for example, 〜), and a positive phrase (for example, agree, agree, ping-pong). positive cases dictionary with a dictionary related to, a result clause (for example, so, so) the results representation case dictionary with a dictionary related to, greeting clause (for example, Hello) greeting case dictionary with a dictionary related to, It is composed of a negative case dictionary having a dictionary related to a negative phrase (for example, it is not stupid, opposite), and each dictionary is associated with a “speech sentence type”.
[0041]
Accordingly, the utterance type determination unit 440 compares the phrase with each dictionary stored in the utterance type database 460, extracts a sentence element related to each dictionary from the phrase, and associates the extracted sentence element with the extracted sentence element. The “utterance sentence type” can be determined by referring to the type of determination.
[0042]
The utterance type determination unit 440 outputs an answer search command signal for causing the corresponding user to search for a specific answer sentence to the answer sentence search unit 370 based on an instruction from the topic search unit 360 described later.
[0043]
The conversation database 500 stores a plurality of pieces of second morpheme information indicating a morpheme composed of one character, a plurality of character strings, or a combination thereof, and a plurality of replies to the user with respect to the utterance content in advance in association with each other. Means (discussion storage means). The conversation database 500 is also an answer storage unit (discussion storage unit) that stores a plurality of answer types indicating the types of each answer content associated with a plurality of answer contents in advance in association with the second morphological information.
[0044]
Further, the conversation database 500 stores in advance a plurality of discourse ranges (keywords) indicating morphemes constituting ranges related to the input contents to be input by the user or the contents of answers to the user. But also. This discourse range (keyword) is associated with a plurality of pieces of second morpheme information indicating a morpheme composed of one character, a plurality of character strings, or a combination thereof, and each piece of the second morpheme information contains an answer to the user. Associated with each.
[0045]
Furthermore, the conversation database 500 is also an answer storage unit (discussion storage unit) that classifies and stores each element constituting the second morphological information into attributes such as a subject composed of a nominative case and a target case composed of a purpose case. .
[0046]
As shown in FIG. 8, in the present embodiment, the conversation database 500 can be roughly divided into a discourse meaning a range that is relevant to the utterance content that will be uttered by the user or the answer content to the user. It is composed of a range (discourse) and a topic (topic) indicating a range most closely related to the content spoken by the user. As shown in the drawing, the “discussion range” is positioned as a higher concept of “topic” in the present embodiment.
[0047]
Each discourse range can be configured to have a hierarchical structure, as shown in FIG. As shown in the figure, for example, the discourse range (entertainment) of a higher concept with respect to a certain discourse range (movie) is arranged in an upper hierarchical structure, and the discourse range of a lower concept with respect to the discourse range (movie) (movie) Attribute, showing movie) can be located in a lower hierarchical structure. That is, in the present embodiment, each discourse range can be arranged at a hierarchical position where the relationship between the superordinate concept, the subordinate concept, the synonym, and the synonym with the other discourse ranges is clear.
[0048]
As described above, the discourse range is composed of each topic. In the present embodiment, for example, if the discourse range is the A movie name, it includes a plurality of topics related to “A movie name”. .
[0049]
This topic means a morpheme composed of one character, a plurality of character strings, or a combination thereof, that is, each morpheme constituting the utterance content that will be uttered by the user. In the present embodiment, It is composed of each morpheme associated with the subject (subject), the object (target case), and the "case" (attribute) of the action. In the present embodiment, each morpheme associated with these three elements is expressed as a topic title (this topic title corresponds to a lower concept of “topic”) (second morpheme information). .
[0050]
The topic title is not limited to each morpheme associated with the above three elements, but may include other "cases", that is, time (tense, aspect) meaning time, location meaning location, Each morpheme may be associated with a condition indicating a condition, an impression indicating an impression, an effect indicating a result, or the like.
[0051]
In this embodiment, the topic title (second morpheme information) is stored in the conversation database 500 in advance, and the first morpheme information (derived from the utterance content uttered by the user) They are distinct.
[0052]
For example, if the topic title has a discourse range of “A movie name”, as shown in FIG. 10, subject (A movie name), object (director), action (great) ｛this is “A movie The name director is made up of｝, which means “great.”
[0053]
If there is no morpheme associated with “case composition” (subject, object, action, etc.) in the topic title, this portion is indicated with “*” in the present embodiment.
[0054]
For example, what is the $ A movie name? When the sentence of｝ is converted into a topic title (subject; object; action), what is the name of ｛A movie? In the sentence of｝, “A movie name” can be specified as the subject, but the other “object” “action” is not an element of the sentence, so the topic title is “subject” (A movie name) No "object"(*); no "action" (*) (see FIG. 10).
[0055]
The answer sentence means an answer sentence (answer content) that answers the user, and is associated with each topic title (second morpheme information) in the present embodiment (see FIG. 8). In this embodiment, as shown in FIG. 11, the answer sentence is a statement (D; Declaration) and an impression sentence (I; Impression) in order to make an answer corresponding to the type of the utterance sentence uttered by the user. , Conditional sentence (C; Condition), result sentence (E; Effect), time sentence (T; Time), place sentence (L; Location), and negative sentence (N; Negation). ing.
[0056]
That is, as shown in FIG. 12, each answer sentence is associated with, for example, the discourse range (Sato) {lower concept; home run, higher concept; grass baseball, synonyms; panda Sato / Sato / Panda} and each topic title Have been.
[0057]
As shown in the figure, for example, the topic title 1-1 is $ (Sato; *; I like): This is the order of (subject; object; action) as described above. If the order is the same as in the following, the answer sentence 1-1 corresponding to the topic title 1-1 is (DA; statement positive sentence "I like Sato"), (IA; impression positive sentence) "I like Sato very much"), (CA; positive statement on condition "Because Sato's home run is very impressive"), (EA; positive statement on result "I always watch TV games where Sato appears"), (TA; Time affirmative sentence "I really like it because of the five consecutive hits in Koshien"), (LA; Place affirmative sentence "I like the serious face when standing on a blow"), (NA Affirmative sentence "I don't want to talk to someone who dislikes Sato, goodbye").
[0058]
In the present embodiment, as shown in FIG. 2, the conversation control unit 300 includes a management unit 310, a reflective determination unit 320, a parrot return determination unit 330, a discourse range determination unit 340, and an abbreviation sentence complementing unit 350. , A topic search unit 360 and an answer sentence search unit 370.
[0059]
The management section 310 controls the entire conversation control section 300. Specifically, the management unit 310 to which the character string signal has been input from the input unit 100 or the voice recognition unit 200 outputs the input character string signal to the morphological extraction unit 410. Further, management section 310 outputs the answer sentence searched by answer sentence search section 370 to output section 600.
[0060]
The reflexive determination unit 320 is a fixed form acquisition unit that compares the first morpheme information extracted by the morpheme extraction unit 410 with each fixed content, and searches for fixed content including the first morpheme information from each fixed content. .
[0061]
Here, the standard content means reflective element information for answering the standard content to the utterance content from the user, and this reflective element information is stored in the reflective element database 801 (standard type storage means) in advance. A plurality is stored. As the reflective element information, in the present embodiment, as shown in FIG. 13, for example, "Good morning", "Hello", "Good evening", "greeting elements" such as "Hey", "I see", "Really?" And "typical elements".
[0062]
Specifically, the reflexive determination unit 320 to which the topic search command signal has been input from the sentence structure analysis unit 430 receives the first morphological information included in the input topic search command signal and each of the information stored in the reflection element database 801. By comparing the reflection element information with the reflection element information, the reflection element information including the first morphological information is searched from each reflection element information, and the searched reflection element information is output to the management unit 310.
[0063]
That is, assuming that the reflection element information is D1 and the first morpheme information is W, the reflection determining unit 320 determines that the relation of W∩D1 ≠ φ (φ; empty set) is satisfied, Perform a process for giving a typical answer.
[0064]
For example, when the user utters the utterance content of “good morning”, the reflexive determination unit 320 compares the utterance content “good morning” with each piece of reflection element information, and from each piece of reflection element information, The reflection element information “good morning” including (matching with) “good morning” is retrieved, and the retrieved reflection element information “good morning” is output to the management unit 310.
[0065]
When it is not possible to search for the reflection element information including the utterance content from each of the reflection element information, the reflexive determination section 320 converts the topic search command signal input from the sentence structure analysis section 430 into a parallax return determination section 330. Output to
[0066]
The parrot return determination unit 330 compares the current first morpheme information extracted by the morpheme extraction unit 420 with past response contents stored in the parrot return element database 802, and determines that the current first morpheme information is a past response. If it is included in the content, it is a standard acquisition means for acquiring the agreement content.
[0067]
Here, in this embodiment, the parrot return means that the content of the utterance of the user is repeated as it is (or a content close thereto). In this embodiment, the parrot return element is composed of first morpheme information and the like constituting the answer content output from the conversation control device 1 immediately before. As shown in FIG. 14, for example, “horse is beautiful” (Horse; *; beautiful) and "I like Sato"(Sato;*; I like it).
[0068]
In addition, the parrot return element database 802 is an agreement storage unit that previously stores agreement details for agreeing to input information input by a user. The contents of the agreement include, for example, the input information previously input by the user (if the previous input information is “Is the director of the A movie name Mr. S?” The director of A movie name is Mr. S)), or "Exactly", "True".
[0069]
Specifically, the parrot return determining unit 330 to which the topic search command signal is input from the reflexive determination unit 320 configures the first morphological information and the parrot return element included in the input topic search command signal for each parrot return element. By comparing each morpheme, it is determined whether or not the first morpheme information is included in the parrot return element (see FIG. 14).
[0070]
When the parrot return determination unit 330 determines that the first morpheme information is included in each parrot return element, it obtains the consensus content and outputs an answer sentence including the obtained consensus content to the management unit 310 (parrot return). Process). That is, assuming that the parrot return element (such as the previous answer sentence) is S and the first morpheme information is W, the parrot return determination unit 330 indicates above when the relationship of W⊂S and W ≠ φ is established. Perform parrot return processing.
[0071]
For example, the conversation control device 1 gives the answer sentence "The director of the A movie name is Mr. S" (the director of the A movie name; Mr. S; *) (the order is subject, object, action, and so on). ) Is output, and then, when the user utters “A is the director of the A movie name Mr. S” (Director of the A movie name; Mr. S; *) in response to the output content, the parrot returns The determination unit 330 determines that the first morpheme information of the user (Director of the A movie name; Mr. S; *) matches each morpheme of the answer sentence (Director of the A movie name; Mr. S; *). The user concludes that the answer is being parroted, obtains the memorized agreement contents such as "exactly," and outputs the acquired agreement contents.
[0072]
Further, the parrot return determining unit 330 compares the current first morphological information extracted by the morphological extracting unit 420 with past first morphological information stored in the parrot return element database 802, and outputs the current first morphological information. Is included in the past first morpheme information, it is also a fixed form acquisition means for acquiring the content of repulsion.
[0073]
Specifically, when the user utters the utterance content that “the horse is beautiful” and the conversation control device 1 outputs the content of “the horse has a sense of dynamism” as the answer content, it is used later. When the person repeats the utterance content “horse is beautiful”, the parrot return determining unit 330 determines that each morpheme (first morpheme information) constituting the current utterance content “horse is beautiful” {horse; Since each morpheme (first morpheme information) {horse; *; beautiful} that constitutes the previous utterance content “horse is beautiful” matches, the user responds from the conversation control device 1 “horse is dynamic. "I have a good feeling."
[0074]
In this case, since the user has not heard the answer content from the conversation control device 1, the parrot return determination unit 330 acquires the stored rebound content (for example, do not repeat the same content) and obtains the acquired repulsion. The contents can be output.
[0075]
On the other hand, when the parrot return determining unit 330 determines that the first morpheme information is the same as the content of the previous answer sentence or that the first morphological information is not the same as the previous first morphological information, the reflexive determining unit 320 The input topic search command signal is output to the discourse range determination unit 340.
[0076]
Although the parrot return determination unit 330 has described the process in the case where the user has performed the parrot return on “the answer content of the conversation control device 1”, the following process can be further performed. For example, when the output unit 600 outputs an answer sentence “Horse is beautiful”, the user responds to this answer with “Why is the horse beautiful?”, “Why is it beautiful?”, Or “Why is it?” This is the process of the parrot return determination unit 330 performed when the user utters.
[0077]
In this case, the parrot return determination unit 330 outputs the answer sentence S “the horse is beautiful” and the utterance content W from the user (“Why is the horse beautiful? (Question sentence)” or “Why is it beautiful? (Question sentence). )), (W−c) ⊂S (where c denotes the utterance type of W, and this utterance type is determined by an utterance type determination unit 440 described later. Is, for example, a question sentence, etc., as will be described later.) Therefore, a “conditional” parrot return process (when a user performs a parrot return with a question sentence to the answer content) Processing).
[0078]
As the “conditional” parrot return processing, for example, when the conversation control device 1 outputs an answer sentence “Horse is beautiful”, the user utters the utterance content “Why is the horse beautiful?” At this time, in order to solve the user's questions and the like, the parrot return determining unit 330 obtains an answer sentence such as “The horse is not beautiful” from the parrot return element database 802, and the obtained answer sentence is stored in the management unit 310. Perform output processing.
[0079]
The discourse range determination unit 340 is a discourse search unit that compares the first morpheme extracted by the phrase analysis unit 420 with each discourse range, and searches for a discourse range including the first morpheme information from each discourse range. .
[0080]
Specifically, the discourse range determination unit 340 to which the topic search command signal is input from the parrot return determination unit 330 determines the user's discourse range based on the input discourse search command signal. That is, the discourse range determination unit 340 searches the conversation database 500 for a range relevant to the content spoken by the user (discussion range) based on the input search command signal.
[0081]
For example, the discourse range determining unit 340 determines that the first morpheme information included in the input topic search command signal is (interesting movie; *; is there) / is there an interesting movie? In the case of｝, the first morpheme information is collated with the discourse range group, and when the discourse range group includes a morpheme (for example, “movie”) constituting the first morpheme information, The "movie" included in the information is determined as the discourse range. In this case, since the discourse range “movie” is included in the first morpheme information, the discourse range determination unit 340 includes the input first morpheme information in the topic search command signal and outputs it to the topic search unit 360.
[0082]
On the other hand, if the discourse range group is not included in the first morpheme information, the discourse range determination unit 340 includes the input first morpheme information in the topic search command signal and outputs it to the abbreviation sentence complementing unit 350.
[0083]
Thereby, the topic search unit 360, which will be described later, checks each “topic title” belonging to the “discussion range” determined by the discourse range determination unit 340 against the first morpheme information specified by the sentence structure analysis unit 430. Therefore, it is not necessary to collate “all” “topic titles” (second morpheme information) with the first morpheme information, and the answer sentence search unit 370 described later performs until the final answer sentence is searched. Time can be shortened.
[0084]
As described above, the discourse range determination unit 340 compares the first morpheme information with the discourse range group, and if the discourse range group includes the morpheme of the first morpheme information, determines the morpheme as the discourse range. However, the present invention is not limited to this, and the morpheme of the parrot return element searched immediately before by the parrot return determination unit 330 or the morpheme constituting the utterance content uttered by the user may be determined as the discourse range. . Using the discourse range determined by the discourse range determination unit 340, the abbreviated sentence complementing unit 350 described below can add the discourse range to the first morpheme information in which the morpheme is omitted.
[0085]
The abbreviated sentence complementing unit 350 searches for an attribute that does not include a morpheme from among the attributes (subject, object, action, etc.) constituting the first morpheme information based on the first morpheme information extracted by the phrase analysis unit 420. Attribute search means. The abbreviation sentence complementing unit 350 is also a morpheme adding unit that adds a morpheme constituting the discourse range searched by the discourse range determination unit 340 to the attribute based on the searched attribute.
[0086]
Specifically, the abbreviation sentence complementing unit 350 to which the topic search command signal has been input from the discourse range determination unit 340, based on the first morpheme information included in the input discourse search command signal, generates an utterance composed of the first morpheme information. It is determined whether the content is an abbreviated sentence, and if the utterance content composed of the first morpheme information is an abbreviated sentence, the morpheme of the discourse range to which the first morpheme information belongs is added to the first morpheme information.
[0087]
For example, the abbreviation sentence complementing unit 350 determines that the morpheme constituting the first morpheme information included in the input topic search command signal is (supervisor; *; *) (supervisor?) Is unknown, meaning an abbreviated sentence.), The discourse range previously determined by the discourse range determination unit 340 (A movie name; this A movie name indicates the title of the movie) If the first morpheme information belongs to the first morpheme information, the determined discourse range (A movie name) is added to the first morpheme information to the morphemes constituting the first morpheme information (director of “A movie name”; *; *).
[0088]
That is, assuming that the first morpheme information is W and the determined discourse range is D, the abbreviation sentence complementing unit 350 adds the discourse range D to the first morpheme information W, and uses the post-addition first morpheme information as a topic search command. It is included in the signal and output to the topic search unit 360.
[0089]
Accordingly, even when the first morpheme information is an abbreviation sentence and is not clear as Japanese, the abbreviation sentence complementing unit 350 may determine that the first morpheme information belongs to a certain discourse range, D (A movie name) is added to the first morpheme information W (director; *; *), and the first morpheme information is W '(director of A movie name; *; *) ｛Who is the director of the A movie name? Because it can be treated as｝, even if the user's utterance content is an abbreviation, the abbreviation can be complemented based on the previously determined discourse range, and the abbreviation should be clarified Can be.
[0090]
For this reason, the abbreviation sentence complementing unit 350 generates the first morpheme information so that even if the utterance content constituting the first morpheme information is an abbreviation, the utterance content constituting the first morpheme information becomes proper Japanese. The topic search unit 360 obtains an optimal “topic title” (second morpheme information) related to the first morpheme information based on the complemented first morpheme information. The answer sentence search unit 370 can output an answer content more suitable for the utterance content of the user based on the “topic title” acquired by the topic search unit 360.
[0091]
The topic search unit 360 collates the first morpheme information extracted by the phrase analysis unit 420 or the first morpheme information complemented by the abbreviation sentence complementing unit 350 with each second morpheme information, It is a first search means for searching for second morpheme information including morphemes constituting the first morpheme information from among them.
[0092]
Specifically, the topic search unit 360 to which the topic search command signal has been input from the discourse range determination unit 340 or the abbreviation sentence complementing unit 350 has the discourse range based on the first morpheme information included in the input topic search command signal. From each "topic title" (second morpheme information) belonging to the discourse range determined by the determination unit 340, a "topic title" including the morpheme of the first morpheme information is searched, and this search result is used as a search result signal. Output to answer sentence search unit 370 and utterance type determination unit 440.
[0093]
For example, if the “case configuration” that constitutes the first morphological information is (Sato; *; like) {I like Sato}, the topic search unit 360 determines the “case” as shown in FIG. The morphemes (Sato; *; I like) belonging to “composition” are compared with the topic titles 1-1 to 1-4 belonging to the discourse range (Sato), and from among the topic titles 1-1 to 1-4, A topic title 1-1 (Sato; *; I like) that matches (or approximates) each morpheme (Sato; *; I like) belonging to "case composition" is searched, and the search result is used as an answer sentence as a search result signal. The data is output to the search unit 370 and the utterance type determination unit 440.
[0094]
The utterance type determination unit 440 to which the search result signal is input from the topic search unit 360 is an answer search command for causing the user to search for a specific answer sentence based on the input search result signal. The signal (the answer search command signal also includes the determined “uttered sentence type”) is output to the answer sentence search unit 370.
[0095]
The answer sentence search unit 370 is an answer acquisition unit that acquires an answer sentence associated with the second morpheme information based on the second morpheme information (topic title) searched by the topic search unit 360. Also, the answer sentence search unit 370 collates the utterance type of the identified user with each answer type associated with the second morpheme information based on the second morpheme information searched by the topic search unit 360, It is also a second search unit that searches for an answer type that matches the utterance type of the user from among the answer types.
[0096]
Specifically, the answer sentence search unit 370 to which the search result signal from the topic search unit 360 and the answer search command signal from the utterance type determination unit 440 have been input, outputs the topic title (search result) corresponding to the input search result signal. Based on the second morphological information) and the "utterance sentence type" (utterance type) corresponding to the answer search command signal, based on the answer sentence group (each answer content) associated with the "topic title". From among them, an answer sentence composed of an answer type (this answer type means "answer sentence type" shown in FIG. 11) matching "uttered sentence type" (DA, IA, CA, etc.) is searched.
[0097]
For example, if the topic title corresponding to the search result is the topic title 1-1 (Sato; *; I like it) shown in FIG. 12, the answer sentence search unit 370 is associated with the topic title 1-1. From the answer sentence 1-1 (DA, IA, CA, etc.), an answer consisting of an answer type (DA) that matches the "utterance sentence type" (for example, DA; utterance type) determined by the utterance type determination unit 440 The sentence 1-1 (DA; (I also like Sato)) is searched, and the searched answer sentence is output to the management unit 310 as an answer sentence signal.
[0098]
The management unit 310 to which the answer sentence signal is input from the answer sentence search unit 370 outputs the input answer sentence signal to the output unit 600. In addition, the management unit 310 to which the reflection element information is input from the reflective judgment unit 320 or the content of the parrot return processing from the parrot return determination unit 330 is input, and the answer sentence corresponding to the input reflection element information, the content of the input parrot return processing Is output to the output unit 600.
[0099]
The output unit 600 is an output unit that outputs the answer sentence obtained by the answer sentence search unit 370. In the present embodiment, for example, a speaker, a display, or the like is used. Specifically, the output unit 600 to which the answer sentence is input from the management unit 310 outputs the input answer sentence {for example, I also like Sato}.
[0100]
(Conversation control method using conversation control device)
The conversation control method by the conversation control device 1 having the above configuration can be performed according to the following procedure. FIG. 15 is a flowchart illustrating a procedure of the conversation control method according to the present embodiment.
[0101]
First, the input unit 100 performs a step of acquiring the utterance content from the user (S101). Specifically, the input unit 100 acquires a voice that constitutes the utterance content of the user, and outputs the acquired voice to the voice recognition unit 200 as a voice signal. The input unit 100 specifies a character string corresponding to the input information (other than voice) based on the input information (other than voice) input from the user, and uses the specified character string as a character string signal as a conversation controller. Output to 300.
[0102]
Next, the voice recognition unit 200 performs a step of specifying a character string corresponding to the utterance content based on the utterance content acquired by the input unit 100 (S102). Specifically, the speech recognition unit 200 to which the speech signal is input from the input unit 100 analyzes the input speech signal, and stores a character string corresponding to the analyzed speech signal in the speech recognition dictionary storage unit 700. The specified character string is output to the conversation control unit 300 as a character string signal.
[0103]
Then, the morpheme extraction unit 410 performs a step of extracting each morpheme constituting the minimum unit of the character string as the first morpheme information based on the character string specified by the speech recognition unit 200 (S103).
[0104]
Specifically, the morpheme extraction unit 410 to which the character string signal has been input from the management unit 310 includes a character string corresponding to the input character string signal and a noun, adjective, verb, or the like stored in the morphological database 450 in advance. The morphemes are collated with each other, each morpheme (m1, m2,...) That matches the morpheme group is extracted from the character string, and each extracted morpheme is output to the phrase analyzer 420 as an extraction signal.
[0105]
Then, the phrase analysis unit 420 performs a step of compiling each morpheme into a phrase format based on each morpheme extracted by the morpheme extraction unit 410 (S104). Specifically, the phrase analysis unit 420 to which the extraction signal is input from the morpheme extraction unit 410 uses the respective morphemes corresponding to the input extraction signal to combine them into a phrase format.
[0106]
That is, as shown in FIG. 4, the phrase analysis unit 420 extracts a dependency element (for example, ga wo wo ...) of each morpheme based on each morpheme corresponding to the input extracted signal and extracts the morpheme. The morphemes are grouped into phrases based on the dependency elements.
[0107]
The phrase analysis unit 420 that compiles each morpheme into each phrase, the sentence structure analysis unit 430 and the utterance type determination unit 440, using the morphological information including each morpheme that summarizes each morpheme and each morpheme that composes each phras as a morphological signal. Output to
[0108]
After that, the sentence structure analysis unit 430 performs a step of classifying each morpheme of the first morpheme information segmented by the phrase analysis unit 420 into attributes such as subject matter and object case (S105). Specifically, the sentence structure analysis unit 430 to which the sentence pattern signal is input from the sentence pattern analysis unit 420, based on each morpheme corresponding to the input sentence pattern signal and the sentence formed by each morpheme, Determine the "case composition".
[0109]
That is, as shown in FIG. 5, for example, when the dependency element of each morpheme is "" or "ha", the sentence structure analysis unit 430 determines that the morpheme before the dependency element is the subject (subject) Or nominative). In addition, for example, when the dependency element of each morpheme is "" or "", the sentence structure analysis unit 430 determines that the morpheme before the dependency element is an object (object).
[0110]
Further, for example, when the dependency element of each morpheme is “do”, the sentence structure analysis unit 430 determines that the morpheme preceding the dependency element is an action (predicate; this predicate is composed of a verb, an adjective, etc.). Is determined.
[0111]
The sentence structure analysis unit 430 that has determined the “case configuration” of each morpheme constituting each phrase, based on the first morpheme information associated with the determined “case configuration”, determines the range of a topic described below. A topic search command signal for specifying is output to topic search section 360.
[0112]
Next, the utterance type determination unit 440 performs a step of specifying an utterance type indicating the type of utterance content based on the phrase specified by the phrase analysis unit 420 (S106). Specifically, the “speech sentence type” (speech type) is determined based on each morpheme corresponding to the sentence pattern signal input from the phrase analysis unit 420 and the clause composed of each morpheme.
[0113]
That is, based on each phrase corresponding to the input sentence pattern signal, the utterance type determination unit 440 collates each phrase with each dictionary stored in the utterance type database 460, and from among each phrase, Extract sentence elements related to the dictionary. The utterance type determination unit 440 that extracts a sentence element related to each dictionary from each phrase determines a “speech sentence type” based on the extracted sentence element.
[0114]
The utterance type determination unit 440 outputs an answer search command signal for causing the corresponding user to search for a specific answer sentence to the answer sentence search unit 370 based on an instruction from the topic search unit 360 described later.
[0115]
Next, the reflexive determination unit 320 performs a step of comparing the first morpheme information extracted by the morpheme extraction unit 410 with each of the fixed contents, and searching for the fixed contents including the first morpheme information from among the fixed contents. (S107: reflective processing).
[0116]
Specifically, the reflexive determination unit 320 to which the topic search command signal has been input from the sentence structure analysis unit 430 receives the first morphological information included in the input topic search command signal and each of the information stored in the reflection element database 801. The reflection element information is compared with the reflection element information (standard content), the reflection element information including the first morpheme information is searched from each reflection element information, and the searched reflection element information is output to the management unit 310.
[0117]
When it is not possible to search for the reflection element information including the first morpheme information from among the respective pieces of reflection element information, the reflexive determination unit 320 determines the topic search command signal input from the sentence structure analysis unit 430 in a parable manner. Output to the unit 330.
[0118]
Next, the parrot return determining unit 330 performs a step of comparing the first morphological information extracted by the morphological extraction unit 410 with each parrot return element, and searching for a parrot return element including the first morphological information from each parrot return element ( S108: parrot return processing).
[0119]
When the parrot return determining unit 330 determines that the first morpheme information is included in each parrot return element, the parrot return element acquires the parrot return element including the first morphological information, and manages an answer sentence including the obtained parrot return element. Output to the unit 310 (parrot return processing). That is, if the parrot return element (response sentence output last time, the utterance content of the previous user's utterance, etc.) is S and the first morpheme information is W, the parrot return determination unit 330 determines that the relationship of W⊂S and W ≠ φ If it is established, the parrot return processing described above is performed.
[0120]
On the other hand, if the parrot return determining unit 330 determines that the first morphological information is not included in each parrot return element, the parrot return determining unit 330 sends the topic search command signal input from the reflective determining unit 320 to the discourse range determining unit 340. Output.
[0121]
Then, the discourse range determination unit 340 performs a step of comparing the first morpheme extracted by the phrase analysis unit 420 with each discourse range, and searching a discourse range including the first morpheme information from each discourse range. (S109).
[0122]
Specifically, the discourse range determining unit 340 to which the topic search command signal has been input from the parrot return determination unit 330 determines, based on the input search command signal, the contents of the conversation database 500 that the user is speaking. Search for a relevant range (discussion range).
[0123]
For example, the discourse range determining unit 340 determines that the first morpheme information included in the input topic search command signal is (interesting movie; *; is there) / is there an interesting movie? In the case of｝, the first morpheme information is collated with the discourse range group, and when the discourse range group includes a morpheme (for example, “movie”) constituting the first morpheme information, The "movie" included in the information is determined as the discourse range. In this case, since the discourse range “movie” is included in the first morpheme information, the discourse range determination unit 340 includes the input first morpheme information in the topic search command signal and outputs it to the topic search unit 360.
[0124]
On the other hand, if the discourse range group is not included in the first morpheme information, the discourse range determination unit 340 includes the input first morpheme information in the topic search command signal and outputs it to the abbreviation sentence complementing unit 350.
[0125]
Next, the abbreviation sentence complementing section 350 selects, from among the attributes (subject, object, action, etc.) constituting the first morphological information based on the first morphological information extracted by the phrase analyzing section 420, an attribute that does not include a morpheme. Perform the step of searching for Thereafter, the abbreviation sentence complementing unit 350 performs a step of adding a morpheme constituting the discourse range previously searched by the discourse range determining unit 340 to the attribute based on the attribute not including the searched morpheme (S110; Completion of abbreviations).
[0126]
Specifically, the abbreviation sentence complementing unit 350 to which the topic search command signal has been input from the discourse range determination unit 340, based on the first morpheme information included in the input discourse search command signal, generates an utterance composed of the first morpheme information. It is determined whether the content is an abbreviated sentence, and if the utterance content composed of the first morpheme information is an abbreviated sentence, the morpheme of the discourse range to which the first morpheme information belongs is added to the first morpheme information.
[0127]
For example, the abbreviation sentence complementing unit 350 determines that the morpheme constituting the first morpheme information included in the input topic search command signal is (supervisor; *; *) (supervisor?) Is unknown, meaning an abbreviated sentence.), The discourse range determined by the discourse range determination unit 340 (A movie name; the A movie name indicates the title of the movie) If the first morpheme information belongs to a certain morpheme information, the morpheme (A movie name) of the determined discourse range is added to the first morpheme information to the morphemes constituting the first morpheme information (director of “A movie name”; *; *).
[0128]
That is, assuming that the first morpheme information is W and the determined discourse range is D, the abbreviation sentence complementing unit 350 adds the discourse range D to the first morpheme information W, and uses the post-addition first morpheme information as a topic search command. It is included in the signal and output to the topic search unit 360.
[0129]
Next, the topic search unit 360 collates the first morpheme information extracted by the phrase analysis unit 420 or the first morpheme information complemented by the abbreviation sentence complementing unit 350 with each second morpheme information, A step of searching the information for second morpheme information including morphemes constituting the first morpheme information is performed (S111).
[0130]
Specifically, the topic search unit 360 to which the topic search command signal has been input from the discourse range determination unit 340 or the abbreviation sentence complementing unit 350 has the discourse range based on the first morpheme information included in the input topic search command signal. From each "topic title" (second morpheme information) belonging to the discourse range determined by the determination unit 340, a "topic title" including the morpheme of the first morpheme information is searched, and this search result is used as a search result signal. Output to answer sentence search unit 370 and utterance type determination unit 440.
[0131]
For example, if the “case configuration” that constitutes the first morphological information is (Sato; *; like) {I like Sato}, the topic search unit 360 determines the “case” as shown in FIG. The morphemes (Sato; *; I like) belonging to “composition” are compared with the topic titles 1-1 to 1-4 belonging to the discourse range (Sato), and from among the topic titles 1-1 to 1-4, A topic title 1-1 (Sato; *; I like) that matches (or approximates) each morpheme (Sato; *; I like) belonging to "case composition" is searched, and the search result is used as an answer sentence as a search result signal. The data is output to the search unit 370 and the utterance type determination unit 440.
[0132]
The utterance type determination unit 440 to which the search result signal is input from the topic search unit 360 is an answer search command for causing the user to search for a specific answer sentence based on the input search result signal. The signal (the answer search command signal also includes the determined “uttered sentence type”) is output to the answer sentence search unit 370.
[0133]
Then, the answer sentence search unit 370 collates the utterance type of the specified user with each answer type associated with the second morpheme information based on the second morpheme information searched by the topic search unit 360, From each answer type, a step of searching for an answer type that matches the utterance type of the user and acquiring an answer sentence associated with the searched answer type is performed (S112).
[0134]
Specifically, the answer sentence search unit 370 to which the search result signal from the topic search unit 360 and the answer search command signal from the utterance type determination unit 440 have been input, outputs the topic title (search result) corresponding to the input search result signal. Based on the second morphological information) and the "utterance sentence type" (utterance type) corresponding to the answer search command signal, based on the answer sentence group (each answer content) associated with the "topic title". From among them, an answer sentence composed of an answer type (this answer type means "answer sentence type" shown in FIG. 11) matching "uttered sentence type" (DA, IA, CA, etc.) is searched.
[0135]
For example, if the topic title corresponding to the search result is the topic title 1-1 (Sato; *; I like it) shown in FIG. 12, the answer sentence search unit 370 is associated with the topic title 1-1. From the answer sentence 1-1 (DA, IA, CA, etc.), an answer consisting of an answer type (DA) that matches the "utterance sentence type" (for example, DA; utterance type) determined by the utterance type determination unit 440 The sentence 1-1 (DA; (I also like Sato)) is searched, and the searched answer sentence is output to the management unit 310 as an answer sentence signal.
[0136]
Next, the management unit 310 to which the answer sentence signal has been input from the answer sentence search unit 370 outputs the input answer sentence signal to the output unit 600. In addition, the management unit 310 to which the reflection element information is input from the reflective judgment unit 320 or the content of the parrot return processing from the parrot return determination unit 330 is input, and the answer sentence corresponding to the input reflection element information, the content of the input parrot return processing Is output to the output unit 600. The output unit 600 to which the answer sentence is input from the management unit 310 outputs the input answer sentence {for example, I also like Sato} (S113).
[0137]
(Operation and effect of the conversation control system and the conversation control method)
According to the invention of the present application having the above-described configuration, the reflexive determination unit 320 collates the first morpheme information constituting the utterance content uttered by the user with each of the pre-stored standard contents, and from among, it is possible to find the standard content including a first morpheme information, reflexive determination unit 320, for example when the first morpheme information is a fixed content such as "Hello" includes the standard content it is possible to answer the same boilerplate content "Hello" or the like.
[0138]
When the utterance content of the user is a fixed content, the reflexive determination unit 320 answers the fixed content (such as greeting), so that the user first communicates with the conversation control device 1. You can enjoy the feeling of communicating.
[0139]
In addition, the parrot return determining unit 330 compares the current first morpheme information with the past answer contents, and if the current first morpheme information is not included in the past answer contents, an agreement stored in advance. Since the content can be acquired, if the input information currently input by the user matches the past answer content, the parrot return determination unit 330 returns the user to the past That the user has re-examined the answer).
[0140]
In this case, the parrot return determination unit 330 obtains the stored agreement content because the user has performed a parrot on the past answer content, and obtains the obtained agreement content (for example, “Yes, it is”). Can be output. Thereby, if the user does not understand the meaning of the answer content output from the conversation control device 1, the user can listen again and listen to the answer content again, so that the user is just talking with another user. You can enjoy such feeling.
[0141]
In addition, the parrot return determination unit 330 compares the current first morpheme information with the past first morpheme information, and obtains the repulsion content when the current first morpheme information is included in the past first morpheme information. When the input information input last time is included in the input information input this time, the user repeatedly inputs the same content as the previous input information. It can be determined that the user has not responded appropriately to the content of the response from the conversation control device.
[0142]
In this case, the parrot return determination unit 330 obtains the stored repulsion content, and obtains the obtained repulsion content in order to repel the user because the user has not properly responded to the previous response content. Is output. As a result, if the user does not input appropriate input information with respect to the answer content from the conversation control device 1, the repulsion content is output from the conversation control device 1, so that the user can speak with another user. You can enjoy the feeling of being.
[0143]
Also, the topic search unit 360 may search each second morpheme information belonging to the “discussion range” with the first morpheme information to search for second morpheme information that is similar to the first morpheme information. It is not necessary to collate the second morpheme information with the first morpheme information, so that the time required to search for second morpheme information similar to the first morpheme information can be reduced.
[0144]
As a result, the topic search unit 360 can quickly search (pinpoint search) for the second morpheme information that is similar to the first morpheme information, so that the answer sentence search unit 360 The answer sentence associated with the second morpheme information can be acquired in a short time based on the retrieved second morpheme information, and the conversation control device 1 quickly answers the utterance content from the user. be able to.
[0145]
Also, the topic search unit 360 searches the second morpheme information for second morpheme information including morphemes constituting the first morpheme information (elements constituting the utterance content of the user), and an answer sentence search unit Since the 370 can acquire the answer content associated with the second morpheme information based on the second morpheme information searched by the topic search unit 360, the answer sentence search unit 370 extracts the utterance content of the user. Based on the constituent morphemes (first morpheme information), it is possible to take into account the semantic space (subject, target, etc.) constructed by each morpheme, and obtain the answer content created in advance based on the semantic space. Thus, it is possible to acquire an answer content more suitable for the utterance content than to simply obtain the answer content associated with the keyword using the entire utterance content as a keyword.
[0146]
Further, since the topic search unit 360 searches for the second morpheme information including the first morpheme information, there is no need to search for the second morpheme information that completely matches the utterance content of the user, and the conversation control device 1 is developed. A developer who does not need to previously store a huge amount of response contents corresponding to the utterance contents that will be uttered by the user, and can reduce the capacity of the storage unit.
[0147]
Further, the answer sentence search unit 370 selects an answer type that matches the utterance type of the user from among the answer types (statements, affirmations, places, repulsions, etc.) associated with each second morpheme information belonging to the “discussion range”. Can be obtained, and the answer content associated with the answer type can be acquired based on the searched answer type. Therefore, the conversation control device 1 sets the utterance type that constitutes the conversation content of the user, for example, Based on a simple opinion, a user's impression, or a user's locational element, a response that matches the user's utterance type is selected from multiple responses. As a result, it is possible to obtain an optimum answer to the corresponding user.
[0148]
Furthermore, the answer sentence search unit 370 selects, from among the answer types associated with each second morpheme information belonging only to the “discussion range” retrieved by the discourse range determination unit 340, an answer that matches the utterance type of the user. Since it is only necessary to search for the type (pinpoint search is possible), there is no need to search for the answer type and the user's utterance type associated with the "all" second morpheme information one by one, and the user's utterance type In a short period of time, it is possible to obtain the optimum answer content corresponding to the above.
[0149]
Finally, the abbreviation sentence complementing unit 350 determines that the first morpheme information belonging to the discourse range where the first morpheme information is present even if the first morpheme information constituting the utterance content of the user is an abbreviation and is not clear as Japanese. If so, the discourse range can be added to the first morpheme information to complement the first morpheme information composed of abbreviations.
[0150]
With this, the abbreviation sentence complementing unit 350 generates the first morpheme information so that the utterance content constituting the first morpheme information becomes proper Japanese even if the utterance content constituting the first morpheme information is an abbreviation sentence. Can be supplemented with a specific morpheme (such as a morpheme constituting the discourse range), the topic search unit 360 determines the first morpheme based on the complemented first morpheme information supplemented by the abbreviation sentence complementing unit 350. The optimal second morpheme information related to the information can be obtained, and the answer sentence search unit 370 determines an answer content more suitable for the utterance content of the user based on the second morpheme information obtained by the topic search unit 360. Can be output.
[0151]
As a result, even if the input information from the user is an abbreviated sentence, the conversation control device 1 uses the past search result without using the functions such as the neural network and the artificial intelligence to determine what the abbreviated sentence means. It is possible to infer whether the conversation control device 1 is to be used, and the developer of the conversation control device 1 does not need to install a neural network and artificial intelligence, so that the system of the conversation control device 1 can be constructed more easily.
[0152]
[Example of change]
It should be noted that the present invention is not limited to the above embodiment, and the following changes can be made.
[0153]
(First modification example)
In the present modification, the conversation database 500 may be an element storage unit that stores a plurality of element information indicating the entire set group including a plurality of morpheme sets in association with the set group. Further, the morpheme extraction unit 410 compares the morpheme extracted from the character string with each set group, selects a set group including the extracted morpheme from each set group, and selects an element associated with the selected set group. Information may be extracted as first morpheme information.
[0154]
As shown in FIG. 16, some morphemes included in a character string uttered by the user are similar. For example, as shown in FIG. 16, when the element information indicating the entire set group is “gift”, the “gift” is similar to a present, a gift, a year-end gift, a gift, a celebration, etc. (set group). Therefore, if there is a morpheme similar to “gift” (such as the above-described present), the morpheme extraction unit 410 can treat the similar morpheme as “gift”.
[0155]
That is, for example, when the morpheme extracted from the character string is “present”, the morpheme extracting unit 410 determines that the element information representing “present” is “gift” as shown in FIG. "Present" can be replaced with "gift".
[0156]
Accordingly, the morpheme extraction unit 410 can sort morphemes similar to each other, so that a developer who develops a conversation control device can use a morpheme extraction unit corresponding to a semantic space grasped from each of the mutually similar first morpheme information. It is not necessary to create answer contents related to the two morpheme information and the second morpheme information one by one, and as a result, the amount of data stored in the storage unit can be reduced.
[0157]
(Second modification example)
As shown in FIG. 17, in this modification, the topic search unit 360 may include a ratio calculation unit 361 and a selection unit 362.
[0158]
The ratio calculator 361 compares the first morpheme information extracted by the morpheme extractor 410 with each second information, and for each second morpheme information, a ratio of the first morpheme information to the second morpheme information. Is a calculation means for calculating.
[0159]
Specifically, as shown in FIG. 17, the ratio calculation unit 361 to which the topic search command signal is input from the sentence structure analysis unit 430, generates a second morpheme information based on the first morpheme information included in the input topic search command signal. The one morpheme information is compared with each topic title (second morpheme information) belonging to the discourse range stored in the conversation database 500, and for each topic title, the first morpheme information occupies each topic title. Calculate the percentage.
[0160]
For example, as shown in FIG. 17, if the first morpheme information constituting the utterance sentence uttered by the user is (Sato; *; I like) {I like Sato}, the ratio calculation unit 361 Each morpheme (Sato; *; I like) belonging to "case composition" is compared with each morpheme (Sato; *; I like) included in the topic title, and each morpheme belonging to "case composition" is added to the topic title. (Sato; *; like) is calculated as 100%. The ratio calculation unit 361 performs these calculations for each topic title, and outputs the calculated ratios to the selection unit 362 as ratio signals.
[0161]
The selection unit 362 is a selection unit that selects one piece of second morpheme information from each piece of second morpheme information according to the magnitude of each ratio calculated for each piece of second morpheme information by the ratio calculation unit 361. is there.
[0162]
Specifically, the selection unit 362 to which the ratio signal is input from the ratio calculation unit 361 selects from among the ratios (element of “case composition” / element of “topic title” × 100) included in the input ratio signal. For example, a topic title having a high ratio is selected (see FIG. 18). The selecting unit 362 that has selected the topic title having a high ratio outputs the selected topic title to the answer sentence searching unit 370 and the utterance type determining unit 440 as a search result signal. The answer sentence search unit 370 acquires an answer sentence associated with the topic title based on the topic title selected by the selection unit 362.
[0163]
Thereby, the selecting unit 362 calculates, for each piece of second morpheme information, a ratio of the first morpheme information to the second morpheme information, and sets the magnitude of each rate calculated for each piece of second morpheme information. Accordingly, one piece of second morpheme information can be selected from each piece of second morpheme information, so that the selecting unit 362 determines that the first morpheme information (those constituting the uttered content of the user) is the second morpheme information. If the second morpheme information having a large proportion of the two morpheme information can be obtained from a plurality of second morpheme information groups, the second morpheme information following the semantic space grasped from the first morpheme information can be more accurately obtained. As a result, the answer sentence search unit 370 can give an optimum answer to the utterance content of the user.
[0164]
Further, since the selecting unit 362 can select a topic title having a high ratio calculated by the ratio calculating unit 361 from a plurality of topic titles, the selecting unit 362 belongs to the “case configuration” included in the utterance sentence of the user. Even if each morpheme and each topic title stored in the conversation database 500 do not completely match, it is possible to acquire a topic title closely related to each morpheme belonging to “case composition”.
[0165]
As a result, the selecting unit 362 can acquire a topic title closely related to the “case configuration” that forms the first morpheme information, so that the developer who develops the conversation control device 1 configures “ It is not necessary to store topic titles that completely match the "case configuration" in the conversation database 500 one by one, so that the capacity of the conversation database 500 can be reduced.
[0166]
Further, the ratio calculation unit 361 calculates the ratio of the first morpheme information to the second morpheme information for each second morpheme information belonging only to the “discussion range” retrieved by the discourse range determination unit 340. , There is no need to calculate the ratio of the first morpheme information to “all” second morpheme information, and the second morpheme information following the semantic space composed of the first morpheme information is acquired in a shorter time. As a result, based on the acquired second morphological information, it is possible to quickly output the optimum answer content to the utterance content from the user.
[0167]
Note that the ratio calculation unit 361 collates each morpheme of the first morpheme information belonging to each classified attribute with each morpheme of the second morpheme information belonging to each attribute stored in advance for each attribute. The first morpheme information may be a first retrieval unit that retrieves second morpheme information that includes each morpheme of the first morpheme information in at least one attribute from the second morpheme information.
[0168]
Specifically, the ratio calculation unit 361 to which the topic search command signal has been input, for each “case” (subject; object; action) of the “case configuration” included in the input topic search command signal, generates the “case”. Is compared with each morpheme belonging to the topic title “case” having the same “case”, and it is determined whether or not the morphemes constituting the “case” are the same.
[0169]
For example, as shown in FIG. 19, when the morpheme of the “case” of the “case configuration” is (dog; person; bites) {the dog bites the person}, the ratio calculation unit 361 Match "dog", "person", "bite" with the morpheme "dog", "person", "bite" of the topic title consisting of "case" which is the same as "case" that composes those morphemes Then, among the morphemes “dog”, “person”, and “bite” constituting the topic title, the morpheme “dog” of “case composition” consisting of the same “case” as the “case” corresponding to each morpheme, Calculate (100%) the percentage that matches “person” and “bite”.
[0170]
If the element composing the topic title is (person; dog; bite) {the person bites the dog}, the ratio calculation unit 361 performs the morpheme belonging to the two cases by the same procedure as described above. Therefore, the degree of matching between the morphemes constituting the “case composition” and the “topic title” for each “case” is calculated to be 33% (see FIG. 19).
[0171]
The ratio calculation unit 361 that has calculated the ratio selects a topic title having a high ratio from among the ratios, and outputs the selected topic title to the answer sentence search unit 370 and the utterance type determination unit 440 as a search result signal.
[0172]
Thereby, the ratio calculation unit 361 divides each morpheme of the first morpheme information belonging to each classified “case configuration” (subject case, target case, etc.) and a topic title stored in advance for each “case”. Since the matching can be performed and the second morpheme information including each morpheme of the first morpheme information in at least one “case” can be searched from each topic title, the ratio calculation unit 361 differs from the normal word order. In the case of utterance contents composed of things, for example, "a person bites a dog", the subject morpheme is "people" and the target morpheme is "dog". The matching second morpheme information can be searched, and the answer content associated with the second morpheme information (person; dog; chewing) {“really?” Or “I do not understand the meaning” etc.} is obtained. can do.
[0173]
That is, the ratio calculation unit 361 can identify the utterance content that is difficult to identify, for example, “people bite a dog” and “dog bite a human”. For the former, for example, "really?" For the latter, for example, "OK?"
[0174]
Further, the ratio calculation unit 361 may search the second morpheme information that includes the morpheme of the first morpheme information in at least one attribute from each of the second morpheme information belonging to the “discussion range”, and thus “all”. Of the second morpheme information, it is not necessary to obtain one second morpheme information, it is possible to obtain the second morpheme information following the semantic space composed of the first morpheme information in a shorter time, As a result, the conversation control device 1 can quickly output the optimum answer content to the utterance content from the user based on the acquired second morpheme information.
[0175]
Note that the selection unit 362 may select one topic title from among the topic titles according to a predetermined priority. The priority means a priority for being selected as a topic title. This priority is determined in advance by the developer at the development stage.
[0176]
(Third modification example)
As shown in FIG. 20, the present modification is not limited to the above-described embodiment and each of the above-described modifications, and includes a communication unit 800 in the conversation control devices 1 a and 1 b and a communication unit via the communication network 1000. A communication unit 900 for transmitting and receiving data to and from the communication unit 800, conversation databases 500b to 500d connected to the communication unit 900, and servers 2a to 2c may be provided (conversation control system).
[0177]
Here, the communication network 1000 means a communication network for transmitting and receiving data, and in the present embodiment, for example, the Internet is used.
[0178]
In this modification, the conversation controllers 1a and 1b, the conversation databases 500b to 500d, and the servers 2a to 2c are limited for convenience. However, the present invention is not limited to this, and another conversation database is provided. Is also good. The servers 2a to 2c store the same contents as those stored in the conversation databases 500a to 500d.
[0179]
As a result, the conversation control unit 300 communicates with the other conversation control devices 1b, the conversation databases 500b to 500d, and the servers 2a to 500d via the communication network 1000 as well as the conversation database 500a arranged inside the conversation control device 1a. 2c, it is possible to search the conversation database 500a for a discourse range related to each morpheme (first morpheme information) belonging to the "case configuration" included in the topic search command signal. Even if it is not possible, by referring to the other conversation control device 1b, the conversation databases 500b to 500d, and the servers 2a to 2c, it is possible to search the discourse range related to the first morpheme information, and An answer sentence more suitable for an uttered sentence can be searched.
[0180]
(Fourth modification)
The sentence structure analysis unit 430 may store, in the conversation database 500, each “case configuration” constituting the identified first morphological information and each morpheme associated with each “case configuration”. The answer sentence search unit 370 may store, in the conversation database 500, each “case configuration” constituting the searched answer sentence and each morpheme associated with each “case configuration”.
[0181]
The discourse range determination unit 340 may store the searched discourse range in the conversation database 500. The topic search unit 360 may store the searched second morphological information in the conversation database 500.
[0182]
The first morpheme information, the second morpheme information, each "case configuration" constituting the first morpheme information or the second morpheme information and each morpheme associated with each "case configuration", and the retrieved answer sentence The constituent “case constituents” and the respective morphemes associated with the respective “case constituents” and the retrieved discourse range can be associated with each other and stored in the conversation database 500 as history morphological information.
[0183]
The abbreviation sentence complementing unit 350 does not include a morpheme from each of the attributes (subject, object, action, etc .; case composition) constituting the first morphological information based on the first morphological information extracted by the phrase analyzing unit 420. An attribute may be searched, and the history morpheme information stored in the conversation database 500 may be added to the attribute based on the searched attribute.
[0184]
Specifically, the abbreviation sentence complementing unit 350 to which the topic search command signal has been input from the discourse range determination unit 340, based on the first morpheme information included in the input discourse search command signal, generates an utterance composed of the first morpheme information. It is determined whether the content is an abbreviated sentence, and if the utterance content composed of the first morpheme information is an abbreviated sentence (for example, the subject, object, or action does not have a predetermined morpheme), the conversation database 500 The stored history form information is added to the first morpheme information.
[0185]
That is, if the subject included in the history form information is S1, the object is O1, the action A1, the discourse range is D1, and the omitted first morpheme information is W, the complemented first morpheme information W1 is S1 @ W , O1 @ W, A1 @ W, or D1 @ W.
[0186]
The topic search unit 360 collates the first morpheme information W1 complemented by the abbreviation sentence complementing unit 350 with each piece of second morpheme information, and selects the first morpheme information from each “topic title” (second morpheme information). The second morpheme information including W1 is searched, and the searched topic title is output as a search result signal to the answer sentence search unit 370 and the utterance type determination unit 440.
[0187]
Thus, even when the utterance content composed of the first morpheme information is an abbreviation and is not clear as Japanese, the abbreviation complementing unit 350 uses the history morphology information stored in the conversation database 500 to Since the morpheme of the omitted first morpheme information can be complemented, the utterance content composed of the omitted first morpheme information can be clarified.
[0188]
For this reason, if the utterance content constituting the first morpheme information is an abbreviation, the abbreviation sentence complementing unit 350 sets the first morpheme information so that the utterance content composed of the first morpheme information becomes proper Japanese. Can be complemented, the topic search unit 360 determines the optimal “topic title” (second morpheme) related to the first morpheme information based on the first morpheme information with the complemented morpheme. Information), and the answer sentence search unit 370 can output an answer content more suitable for the utterance content of the user based on the optimal “topic title” acquired by the topic search unit 360. .
[0189]
(Fifth modification example)
As shown in FIG. 21, the topic search unit 360 may include a deletion unit 361 and a discourse addition unit 362. The deletion unit 361 compares the second morpheme information with the discourse range retrieved by the discourse range determination unit 340 based on the retrieved second morpheme information, and selects a discourse from among the morphemes constituting the second morpheme information. This is a deletion unit that deletes a morpheme that matches the range.
[0190]
Specifically, the topic search unit 360 to which the topic search command signal is input from the abbreviation sentence complementing unit 350 receives the first morpheme information included in the input topic search command signal and the discourse determined by the discourse range determination unit 340. Each second morpheme information belonging to the range is collated, and second morpheme information that matches the first morpheme information is searched from each second morpheme information.
[0191]
Then, based on the retrieved second morpheme information, the deletion unit 361 collates the second morpheme information with the morphemes constituting the discourse range determined by the discourse range determination unit 340, and , The morpheme that matches the morpheme constituting the discourse range is deleted, and the second morpheme information from which the morpheme has been deleted is output to the discourse adding unit 362 as a deletion signal.
[0192]
That is, the deletion unit 361 removes (removes) the current discourse range D2 (this D2 is made up of morphemes) determined by the discourse range determination unit 340 from each morpheme t1 constituting the second morpheme information. Assuming that the result is t2, t2 = t1-D2).
[0193]
The discourse adding unit 362 obtains another discourse range associated with the discourse range searched by the discourse range determination unit 340 based on the second morpheme information from which the morpheme has been deleted by the deletion unit 361, and obtains another obtained discourse range. This is a discourse adding means for adding morphemes constituting the discourse range to the second morpheme information.
[0194]
Specifically, assuming that the discourse range in which the current discourse range D2 is related to the answer sentence K1 is DK, another discourse having a relevance (one having a sibling relationship) to the answer sentence K1 or the current discourse range D2. Since the range D3 can be expressed as D3 = D2∪DK, the second morpheme information W2 after adding the morphemes constituting the other discourse range D3 can be expressed as W2 = t2∪D3.
[0195]
For example, each morpheme t1 constituting the second morpheme information is (A movie name; *; interesting) ｛Is the A movie name interesting? If the current discourse range D2 determined by the discourse range determination unit 340 is (A movie name), the deletion unit 361 first determines from each morpheme t1 (A movie name; *; interesting). The discourse range D2 (A movie name) is deleted, and the deleted result is set as t2 (*; *; interesting) (t2 = t1-D2).
[0196]
If the other discourse range D3 related to the current discourse range D2 (A movie name) is “B movie name”, the second morpheme information after adding the morphemes constituting the other discourse range D3 Since W2 is t2∪D3, (B movie name; *; interesting) ｛B movie name is interesting? ｝.
[0197]
Accordingly, when the user's utterance content is “Is the A movie name interesting?”, The discourse adding unit 362 matches each morpheme (A movie name; *; interesting) constituting the user's utterance content. The second morpheme information (A movie name; *; interesting), and the other second morpheme information (B movie name; *; interesting)？ Is the B movie name interesting? Since it can be changed to｝, the answer sentence search unit 370 acquires the answer sentence (for example, “B movie name is interesting”) associated with the second morpheme information changed by the discourse adding unit 362, The obtained answer sentence can be output.
[0198]
As a result, the answer sentence search unit 370 does not output an answer sentence to the utterance content of the user, but relates to the utterance content based on the second morpheme information including the morpheme added by the discourse addition unit 362. Since the answer sentence can be output, the output unit 600 can output a more human-like answer sentence based on the answer sentence searched by the answer sentence search unit 370.
[0199]
Note that the discourse adding unit 362 is not limited to the one that adds another discourse range to the second morpheme information from which the morpheme has been deleted, and the history morpheme information (conversation) (Stored in the database 500).
[0200]
(Sixth modification example)
If the second morpheme information including the first morpheme information cannot be searched from the second morpheme information, the topic search unit 360 collates the first morpheme information with each answer content, and If the answer content including the first morpheme information can be searched from among the above, the first search means for acquiring the second morpheme information associated with the searched answer content may be used.
[0201]
Specifically, the topic search unit 360, to which the topic search command signal is input from the abbreviation sentence complementing unit 350, based on the first morpheme information included in the input topic search command signal, If the second morpheme information matching the first morpheme information cannot be obtained from each of the second morpheme information by comparing the morpheme information, as shown in FIG. The answer sentence associated with the second morphological information is collated.
[0202]
By this collation, when the topic search unit 360 determines that the morpheme (action or morpheme associated with the action) constituting the first morpheme information is included in the answer sentence, Search for the associated second morpheme information.
[0203]
Thus, even if the topic search unit 360 cannot search for the second morpheme information that matches the first morpheme information from each of the second morpheme information, the topic search unit 360 can search for the first morpheme information from each answer sentence. Can be identified, and the second morpheme information associated with the identified answer sentence can be searched, so that the utterance content of the user can be specified. Can be appropriately searched for the second morpheme information corresponding to the first morpheme information that constitutes.
[0204]
As a result, the topic search unit 360 can search for the optimum second morpheme information corresponding to the first morpheme information, so that the answer sentence search unit 370 determines the optimum second morpheme information searched for by the topic search unit 360. , It is possible to acquire an appropriate answer content for the utterance content of the user.
[0205]
[Control program]
The contents described in the conversation control system and the conversation control method can be realized by executing a dedicated program for using a predetermined program language on a general-purpose computer such as a personal computer.
[0206]
Here, in the present embodiment, as the program language, the topic desired by the user, the degree of emotion of the user in a certain matter, or the type of statement, affirmative sentence, question sentence, repellent sentence, etc. For example, a language for hierarchically storing in a database in association with a morpheme according to the above, such as DKML (Discoverse Knowledge Markup Language), XML (extensible Markup Language), and C language developed by the inventors.
[0207]
That is, the conversation control device 1 stores data stored in each of the conversation databases 500a to 500d (storage information such as second morphological information, fixed contents, answer sentences, answer types, sets, discourse ranges, and element information), and others. Can be realized by constructing a DKML (Discoverse Markup Language) or the like and executing a program for utilizing the constructed storage information and the like.
[0208]
According to such a program according to the present embodiment, each morpheme constituting the utterance content of the user is identified, the semantic content grasped from each identified morpheme is analyzed, and the morpheme is associated with the analyzed semantic content. In general, a conversation control device, a conversation control system, and a conversation control method that have an operation effect of outputting an optimal response content corresponding to a user's utterance content by outputting a pre-created response content are generally used. It can be easily realized with a simple general-purpose computer.
[0209]
Further, the developer who develops the conversation control device 1 can hierarchically construct the second morphological information and the like for searching for the answer content to the utterance content of the user in the database using the language, The conversation control device 1 can acquire the answer content to the utterance content from the database through a hierarchical procedure based on the utterance content of the user.
[0210]
That is, the conversation control device 1 determines and determines the hierarchy of the utterance contents of the user (for example, whether the second morpheme information stored in the database is in a higher concept or a lower concept). An appropriate answer content can be obtained from each answer content stored in advance based on the hierarchy.
[0211]
For this reason, the conversation control device 1 does not collate the first morpheme information composed of the utterance content of the user with the “all” second morpheme information stored in advance, and each of the morpheme information belonging to a certain specific hierarchy. Since the second morpheme information and the first morpheme information need only be collated, the second morpheme information similar to the first morpheme information can be obtained in a short time.
[0212]
Further, in the communication between the communication unit 800 and the communication unit 900, data may be transmitted and received via the communication network 1000 using a protocol such as DKML. Thereby, for example, when there is no answer content suitable for the user's utterance content in the conversation control device 1, the conversation control device 1 is adapted to the user's utterance content through the communication network 1000 in accordance with a convention such as DKML. The searched answer contents (written in DKML or the like) can be searched, and the searched answer contents can be acquired (see FIG. 20).
[0213]
Note that the program can be recorded on a recording medium. As shown in FIG. 23, the recording medium includes, for example, a hard disk 1100, a flexible disk 1200, a compact disk 1300, an IC chip 1400, a cassette tape 1500, and the like. According to the recording medium on which such a program is recorded, it is possible to easily store, transport, and sell the program.
[0214]
[Second embodiment]
(Basic configuration of information processing system)
A second embodiment of the present invention will be described with reference to the drawings. FIG. 24 shows the internal structure of the information processing system (conversation control system) according to the present embodiment. As shown in the figure, the information processing system has almost the same internal structure as the conversation control device 1 (information processing device) in the first embodiment, but the conversation control unit 300 has a ranking unit 380 (ranking means). In that it has Except for this difference, the structure is the same as that of the first embodiment and the modified example, and the description of the structure other than the difference will be omitted.
[0215]
In the first embodiment, the process in which the conversation control device 1 acquires the optimum answer sentence corresponding to the input information based on the input information from the user has been described. A process in which the ranking unit 380 ranks the degree of emotion or the like held by the user based on input information from the user will be described. The specific description is as follows.
[0216]
The ranking section 380 ranks the degree of emotion for the user based on the input information input from the user. In the present embodiment, as shown in FIG. It has a unit 381, an understanding state determination unit 382, and a confrontation state determination unit 383. Here, the emotion level means the level of the emotion that the conversation control device 1 has for the input information. In the present embodiment, the emotion level is uniquely determined by the emotion state determination unit 381 described later based on the input information.
[0217]
The ranking unit 380 determines the degree of emotion or the like held by the user based on the “discussion event” table stored in the discourse database. Here, as shown in FIG. 25, the “discussion event” table includes a cohesion factor (cohere) indicating that the first morpheme information is a factor having relevance (cohesion) with the discourse range in the present embodiment. It consists of a topic change (shift) indicating that the first morpheme information is a factor that is not relevant to the current discourse range.
[0218]
Specifically, as shown in FIG. 26, in the present embodiment, the unity factor includes a unity factor (-) and a unity factor (+). As shown in the figure, the unity factor (-) is obtained by searching the topic search unit 360 for a topic title in which the first morphological information belongs to the previous discourse range and is associated with “low emotion level” belonging to the topic title. Means that Here, "low emotion level" means that the conversation control apparatus 1 sets a low emotion level for the topic title (for example, when the conversation control apparatus 1 has little interest in the topic title). Means that
[0219]
As shown in the figure, the unity factor (+) is obtained by searching the topic search unit 360 for a topic title whose first morpheme information belongs to the previous discourse range and which is associated with “high emotion level” belonging to the discourse range. Means that Here, "high emotion level" means that the conversation control apparatus 1 sets a high emotion level for the topic title (for example, when the conversation control apparatus 1 is interested in the topic title). Means that.
[0220]
As shown in FIG. 26, these unity factors (−) and (+) are ranked based on the result of the “conditional” parrot return process by the parrot return determination unit 330 and the result of the abbreviation sentence completion process by the abbreviation sentence complementing unit 350. It is determined by the unit 380.
[0221]
The topic change includes a topic change (-) and a topic change (+) as shown in FIG. The topic change (−) means that the current topic title searched by the topic search unit 360 has been changed to another topic title associated with “low emotion level” later, as shown in FIG. .
[0222]
The topic change (+) means that the current topic title searched by the topic search unit 360 has been changed to another topic title associated with “high emotion level” later, as shown in FIG. . These topic changes (−) and (+) are determined by the ranking unit 380 based on the search results of the discourse range by the discourse range determination unit 340, as shown in FIG.
[0223]
In addition, in addition to the above, the "discussion range event" table indicates that the first morpheme information is an interrupt factor indicating that the current topic is interrupted, and that the first morpheme information is more difficult than the second morpheme information. And the opposition factor indicating that the first morpheme information is a contradictory factor to the second morpheme information.
[0224]
As shown in FIG. 24, the interruption factor is determined by the ranking section 380 based on the parrot return processing by the parrot return determination section 330 and the reflective processing by the reflective determination section 320. The difficulty factor is determined by the ranking unit 380 based on the search result of the topic title (second morpheme information) by the topic search unit 360. The conflict factor is determined by the ranking unit 380 based on the determination of the utterance type by the utterance type determination unit 440.
[0225]
The emotion state determination unit 381 ranks the second morpheme information including the first morpheme information from each second morpheme information based on the search result obtained by the topic search unit 360 according to the frequency of the search. This is a ranking means.
[0226]
The emotional state determination unit 381 is also a ranking unit that ranks a low rank when the search frequency is low, and ranks a high rank when the search frequency is high. The magnitude of this rank can be expressed as the degree of emotion for the user, the degree of understanding of the input information, and the degree of conflict felt by the user.
[0227]
In the present embodiment, the degree of emotion determined by the emotion state determination unit 381 can be ranked in six stages as shown in FIG. 27, for example. This emotion degree is positioned in a direction in which the numerical value shown in the figure increases as the emotion degree held by the user increases (in a direction in which the user improves).
[0228]
Therefore, the transition of the degree of emotion from e (0) to e (3) means that the degree of emotion held by the user increases. On the other hand, a transition of the degree of emotion from e (0) to e (-2) means that the degree of emotion held by the user decreases. In the present embodiment, it is assumed that the reference degree of emotion among the six levels is e (0).
[0229]
In addition, in this embodiment, ranking of the degree of emotion is performed using emotion minus factors, emotion plus factors, and topic change (+) (-). In the present embodiment, the emotion minus factor is assumed to be the interruption factor, the esoteric factor, the confrontation factor, the unity factor (-), and the topic change (-) described above. The emotion plus factor is composed of a unity factor (+) and a topic change (+).
[0230]
In the same figure, the degree of emotion is changed by two or more steps due to the topic change (-) (+). This is because "the degree of emotion is very low" or "the degree of emotion is very low" from the current topic title. When a topic title associated with “high” is selected, the emotion level is changed by two or more levels.
[0231]
Specifically, when the topic search unit 360 does not search for the second morpheme information including the first morpheme information, the emotion state determination unit 381 ranks the degree of emotion held by the user at a lower rank.
[0232]
That is, the fact that the topic search unit 360 does not search for the second morpheme information including the first morpheme information means that the first morpheme information constituting the input information input by the user is stored in advance in each of the second morpheme information. The emotional state determination unit 381 determines that the input information (first morphological information) input by the user is an emotion minus factor (difficulty factor). And set the degree of emotion to the user to be lower.
[0233]
On the other hand, when the topic search unit 360 searches for the second morpheme information including the first morpheme information, the emotion state determination unit 381 ranks the degree of emotion held by the user at a higher rank.
[0234]
That is, the fact that the topic search unit 360 has searched for the second morpheme information including the first morpheme information means that the first morpheme information constituting the input information input by the user is stored in advance in each of the second morpheme information. Since it is possible to artificially determine that the information is easier than the information, the emotional state determination unit 381 determines that the input information input by the user can be understood, and To the higher one.
[0235]
In addition, the emotional state determination unit 381 is also a ranking unit that ranks based on the determination result by the discourse range determination unit 340 (relevance determination unit). In the present embodiment, the discourse range determination unit 340 compares the first discourse range indicating the searched discourse range with the second discourse range indicating the discourse range searched thereafter, and determines that the second discourse range is the first discourse range. This is a relevance determining means for determining whether or not the range is relevant.
[0236]
Specifically, when the discourse range determination unit 340 determines that the second discourse range is not related to the first discourse range, the emotion state determination unit 381 determines, for example, the degree of emotion held by the user. Rank in the lower rank.
[0237]
That is, the fact that the discourse range determination unit 340 determines that the second topic range is not related to the first topic range means that the current discourse range including the first morpheme information (second discourse range) Is different from the discourse range (the first discourse range) (the topic in context does not have cohesion; this is also referred to as “topic change”). 381 indicates that if the first morpheme information belonging to the second discourse range is included in the topic title (second morpheme information) associated with “low emotion level”, the first morpheme information is reduced by an emotion minus factor (topic change ( −)), And set a lower emotion level for the user (see FIGS. 26 and 27).
[0238]
Thereby, the topic change (-) indicates that the current discourse range is changed to another discourse range, and that the first morpheme information belonging to the changed discourse range is not interesting to the conversation control device 1. means.
[0239]
In this case, if the first morpheme information belonging to the second discourse range is included in the topic title (second morpheme information) associated with “high emotion level”, the emotion state determination unit 381 determines that the first morpheme information is It is also possible to determine that the emotion is a positive factor (change of topic (+)), and set the degree of emotion to the user to be higher.
[0240]
Thus, the topic change (+) means that the current discourse range is changed to another discourse range, and the first morpheme information belonging to the changed discourse range is an interesting content for the conversation control device 1. I do.
[0241]
On the other hand, when the discourse range determination unit 340 determines that the second discourse range is related to the first discourse range, the emotion state determination unit 381 assigns the degree of emotion to the user to a higher rank, for example. Rank.
[0242]
That is, the fact that the discourse range determination unit 340 determines that the second topic range has relevance to the first topic range means that the current discourse range including the first morpheme information (the second discourse range) is the previous one. Since it can be quasi-determined that they are substantially the same as the discourse range (the first discourse range) (the contextual topic has cohesion), the emotional state determination unit 381 sets the second discourse range If the first morpheme information belonging to is included in the topic title (second morpheme information) associated with “high emotion level”, it is determined that the first morpheme information is an emotion plus factor (cohesion factor (+)) Then, the degree of emotion held by the user is set to the higher one (see FIGS. 26 and 27).
[0243]
Thus, the unity factor (+) is that the current discourse range is substantially the same as the previous discourse range, and the first morpheme information belonging to the current discourse range is an interesting content for the conversation control device 1. Means
[0244]
In this case, if the first morpheme information belonging to the second discourse range is included in the topic title (second morpheme information) associated with “low emotion level”, the emotion state determination unit 381 determines that the first morpheme information is It is also possible to determine that the emotion is a negative factor (cohesion factor (-)) and set the degree of emotion to the user to be lower.
[0245]
Thus, the unity factor (-) is such that the current discourse range is substantially the same as the previous discourse range, but the first morpheme information belonging to the current discourse range is not interesting to the conversation control device 1. It means there is.
[0246]
The emotional state determination unit 381 is also a ranking unit that ranks the ranks based on the result obtained by adding the morphemes constituting the discourse range in the abbreviation sentence complementing unit 350 to the first morpheme information.
[0247]
Specifically, the abbreviation sentence complementing unit 350 extracts a morpheme from each of the attributes (a subject case composed of a nominative case, a target case composed of a purpose case, etc.) constituting the first morphological information extracted by the sentence structure analyzing unit 430. Search for attributes not included. The abbreviation sentence complementing unit 350 adds, based on the retrieved attribute, a morpheme constituting the discourse range searched by the discourse range determination unit 340 to the attribute.
[0248]
When the morpheme constituting the discourse range is added to the first morpheme information by the abbreviation sentence complementing unit 350, the emotion state determination unit 381 ranks the degree of emotion held by the user at a higher rank.
[0249]
That is, in the abbreviation sentence complementing unit 350, the input information consisting of the first morpheme information is the abbreviation sentence (when the discourse range is added to the first morpheme information, the input information consisting of the first morpheme information before this morpheme is added) Means that the information is an abbreviated sentence) means that the user enters input information belonging to the current discourse range, assuming that it belongs to the current discourse range. Therefore, the input information input at this stage is likely to be an abbreviated sentence in which the morpheme comprising the current discourse range is omitted (for details, refer to the "abbreviated sentence in the first embodiment"). Complement section 350 ").
[0250]
Therefore, when the abbreviation sentence complementing unit 350 determines that the first morpheme information is an abbreviation, the emotional state determination unit 381 determines that the current discourse range is substantially the same as the previous discourse range. The first morpheme information is determined to be a cohesive factor having relevance to the previous discourse range. In this case, if the unity factor is the unity factor (+), the emotion state determination unit 381 sets the degree of emotion to the user to be higher, and if the unity factor is the unity factor (-), It is possible to set a lower emotion level for the user.
[0251]
Further, based on the search result by the reflexive judgment unit 320 or the parrot return judgment unit 330, the emotional state judgment unit 381 ranks the fixed content including the first morphological information or the parallax return element in accordance with the frequency of the search. It is also a means of ranking. The reflexive determination unit 320 is a fixed form acquisition unit that collates the extracted first morphological information with each fixed form content, and searches each fixed form content for reflective element information including the first morphological information.
[0252]
Specifically, when the reflexive determination unit 320 searches for the fixed content that matches the first morpheme information from among the fixed content, the emotional state determination unit 381 ranks the user with a lower degree of emotion. Rank.
[0253]
That is, the fact that the reflexive determination unit 320 has searched for the fixed content that matches the first morpheme information implies that the first morpheme information is an element (interruption factor) for interrupting the current topic. Therefore, the emotional state determination unit 381 determines that the first morpheme information is an emotion minus factor (interruption factor), and sets the emotion level to the user to be lower (see FIG. 26, FIG. 27). For example, if the user inputs "good morning" (regular content) which is completely unrelated to the topic during the conversation, "good morning" becomes a cause of interruption.
[0254]
Further, the parrot return determining unit 330 determines that the current first morphological information extracted by the morphological extracting unit 410 is the past answer content extracted by the morphological extracting unit 410 (this past first morphological information (parrot returning element) (Stored in the parrot return element database 802).
[0255]
When the parrot return determining unit 330 determines that the current first morpheme information is included in the past answer contents, the emotional state determining unit 381 returns the user in a parrot to the past answer contents (the user It is possible to quasi-determine that the first morphological information is the interruption factor for interrupting the current topic.
[0256]
In this case, since the current first morpheme information is an emotion minus factor (interruption factor), the emotion state determination unit 381 sets the degree of emotion held by the user to be lower. (See FIGS. 26 and 27).
[0257]
Further, the parrot return determination unit 330 includes the current morpheme information extracted by the morpheme extraction unit 410 in past first morpheme information (this past first morpheme information is stored in the parrot return element database 802). When the emotion state determination unit 381 determines that the current first morpheme information is included in the past first morpheme information, the emotion state determination unit 381 determines that the user is the same as the past input information regardless of the current topic. It can be determined that the input information has been repeatedly input.
[0258]
In this case, the emotional state determination unit 381 determines that the input information repeatedly input is the cause of the interruption, and sets the degree of emotion to the user to be lower (see the first embodiment for details). (See "Parrot return processing").
[0259]
If the parrot return determination unit 330 or the reflexive determination unit 320 cannot search for the fixed content that matches the first morpheme information from each fixed content, the emotional state determination unit 381 determines the degree of emotion held by the user. May be ranked at a lower rank.
[0260]
Further, when the input information specified by the utterance type determination unit 440 is a repulsive element such as a repulsive sentence, the emotional state determination unit 381 ranks the degree of emotion held by the user at a lower rank. is there.
[0261]
Here, the repulsion element means an element for the user to repel the response content output from the conversation control device 1, and in the present embodiment, for example, the input information of the user It consists of a repellent sentence indicating that the sentence is repulsive to the content, a negative sentence indicating that the input information of the user is a negative sentence for the answer content, and the like.
[0262]
That is, the fact that the input type of the input information input by the user is specified by the utterance type determination unit 440 to be a repulsive element means that the user and the conversation control device 1 are opposed. The emotional state determination unit 381 determines that the first morpheme information is an emotion minus factor (conflict factor), and determines that the degree of emotion held by the user is lower. It is set (see FIGS. 26 and 27).
[0263]
When the topic search unit 360 does not search the second morpheme information including the first morpheme information from the respective second morpheme information, the understanding state determination unit 382 determines that the input information input by the user is difficult. (Difficulty factor) and ranks the understanding level of the input information to a lower rank.
[0264]
That is, the fact that the second morpheme information including the first morpheme information is not searched from among the second morpheme information by the topic search unit 360 means that the first morpheme information is more difficult than the second morpheme information. Since the determination can be made, the understanding state determination unit 382 determines that the first morpheme information is a difficult factor, and sets the understanding level of the input information to a lower level.
[0265]
When the topic search unit 360 searches for the second morpheme information including the first morpheme information from each of the second morpheme information, the understanding state determination unit 382 easily converts the input information input by the user. May be determined, and the level of understanding of the input information may be ranked higher. When the first morpheme information is a factor that causes a topic change to a cohesion factor, the understanding state determination unit 382 may rank the understanding level of the input information to a higher rank.
[0266]
Here, the degree of understanding means the degree of understanding of the input information input by the user. As shown in FIG. 28, this understanding can be ranked in, for example, four stages in the present embodiment.
[0267]
The larger the numerical value (the direction from r (−2) to r (1)), the more the input information is understood (the direction toward clearer understanding). On the other hand, the smaller the numerical value (r (1) to r (-2)), the more the input information is not understood (the direction in which the understanding is unclear).
[0268]
Specifically, as shown in the figure, when the first morpheme information is determined to be an esoteric factor based on r (0), the understanding state determination unit 382 shifts the understanding level to a lower level ( If the first morpheme information is determined to be a factor that changes the topic to a cohesion factor, the understanding level is shifted to a higher level.
[0269]
When the understanding state determination unit 382 determines that the first morpheme information is an interruption factor or a confrontation factor, the first morpheme information does not contribute to the understanding of the input information. Maintain as is (see figure). Furthermore, when the emotion level shifts in the positive direction, the understanding state determination unit 382 shifts the rank of the understanding level to a higher rank.
[0270]
Note that the esoteric factor, unity factor, topic change, interruption factor, and confrontation factor are the same as the contents described in the section of the emotional state determination unit 381, and a description thereof will not be repeated.
[0271]
When the input information specified by the utterance type determination unit 440 is a repulsion element (oppose; also referred to as a confrontation factor) such as a repulsion sentence, the confrontation state determination unit 383 ranks the degree of confrontation with the user high. Is to be ranked. When the input information specified by the utterance type determination unit 440 is not a repulsion element such as a repulsion sentence, the conflict state determination unit 383 ranks the degree of conflict with the user at a lower rank. .
[0272]
Here, the degree of conflict means the degree of conflict that the conversation control device 1 has for the user. As shown in FIG. 29, in the present embodiment, the degree of conflict can be ranked, for example, in five stages. The higher the value, the lower (weaker) the degree of confrontation with the user. On the other hand, it means that the smaller the numerical value, the higher (stronger) the degree of conflict with the user.
[0273]
Specifically, as shown in the figure, when the first morpheme information is determined to be a conflicting factor, the conflicting state determination unit 383 transitions to a lower conflicting level (O (0)) (see FIG. (With ranking). In addition, when the conflict state determination unit 383 determines that the first morpheme information is not a conflict factor but a factor (not a repulsive element) that changes the discourse into a cohesion factor, the conflict level is shifted to a higher one. .
[0274]
Furthermore, when the emotion level for the first morpheme information is set in a higher direction by the emotion state determination unit 381, the conflict state determination unit 383 may set the conflict level to a lower (weaker) level. it can. When the emotion level for the first morpheme information is set in a lower direction by the emotion state determination unit 381, the conflict state determination unit 383 may set the conflict level to a higher (stronger) level. it can.
[0275]
Further, when the first morpheme information is the interruption factor or the esoteric factor, the conflict state determination unit 383 sets the rank of the conflict degree as it is because the first morpheme information does not repel the answer content. (See the figure).
[0276]
The emotion state determination unit 381, the understanding state determination unit 382, or the conflict state determination unit 383 outputs the determined emotion level, understanding level, and conflict level to the output unit 600, and the output unit outputs the input emotion level, understanding level, and understanding level. The degree and the degree of conflict are displayed.
[0277]
(Information processing method using information processing system)
The information processing method by the information processing system having the above configuration can be implemented by the following procedure. FIG. 30 is a flowchart showing the procedure of the ranking method according to the present embodiment.
[0278]
As shown in the figure, first, the input unit 100 performs a step of acquiring input information input by a user (S201). Then, the morpheme extraction unit 410 performs a step of extracting each morpheme constituting the input information based on the input information acquired by the input unit 100 (S202).
[0279]
Thereafter, the sentence structure analysis unit 430 performs a step of compiling each morpheme into a phrase form based on each morpheme extracted by the morpheme extraction unit 410 (S203). In this embodiment, each morpheme belonging to one phrase format is the first morpheme information.
[0280]
Next, the reflexive determination unit 320 performs a step of performing reflexive processing based on the first morpheme information specified by the sentence structure analysis unit 430 (S204, S205). Then, the parrot return determining unit 330 performs a step of performing a parrot return process or a conditional parrot return process based on the first morpheme information specified by the sentence structure analysis unit 430 (S206).
[0281]
Thereafter, the discourse range determination unit 340 performs a step of comparing the first morpheme information with each discourse range and searching for a discourse range including the first morpheme information from each discourse range (S207). Further, when the input information consisting of the first morpheme information is an abbreviation sentence, the abbreviation sentence complementing unit 350 performs a step of adding a morpheme consisting of a discourse range to this first morpheme information (S208).
[0282]
Then, the topic search unit 360 collates the first morpheme information with each piece of the second morpheme information based on the specified first morpheme information or the first morpheme information to which the morpheme is added, and A step of searching for second morpheme information including the first morpheme information from among them is performed (S209). The specific processing of S201 to S208 is the same as the content of the "conversation control method" described in the first embodiment, and thus the details of these processing are omitted.
[0283]
Next, based on the search result by the reflexive determination unit 320, the parrot determination unit 330, the discourse range determination unit 340, the abbreviation sentence complementation unit 350, or the topic search unit 360, the emotion state determination unit 381 determines the degree of emotion held for use. Is performed (S210). Specifically, when the topic search unit 360 does not search for the second morpheme information including the first morpheme information, the emotion state determination unit 381 ranks the degree of emotion held by the user at a lower rank.
[0284]
That is, the fact that the topic search unit 360 does not search for the second morpheme information including the first morpheme information means that the first morpheme information constituting the input information input by the user is stored in advance in each of the second morpheme information. The emotional state determination unit 381 determines that the input information (first morphological information) input by the user is an emotion minus factor (difficulty factor). And set the degree of emotion to the user to be lower.
[0285]
On the other hand, when the topic search unit 360 searches for the second morpheme information including the first morpheme information, the emotion state determination unit 381 ranks the degree of emotion held by the user at a higher rank.
[0286]
That is, the fact that the topic search unit 360 has searched for the second morpheme information including the first morpheme information means that the first morpheme information constituting the input information input by the user is stored in advance in each of the second morpheme information. Since it is possible to artificially determine that the information is easier than the information, the emotional state determination unit 381 determines that the input information input by the user can be understood, and To the higher one.
[0287]
In addition, the emotion state determination unit 381 can also perform a step of ranking the degree of emotion held by the user based on the determination result by the discourse range determination unit 340. In the present embodiment, the discourse range determination unit 340 compares the first discourse range indicating the searched discourse range with the second discourse range indicating the subsequently searched discourse range, and determines that the second discourse range is the first discourse range. It is determined whether or not there is a relationship with the range.
[0288]
Specifically, when the discourse range determination unit 340 determines that the second discourse range is not relevant to the first discourse range, the emotion state determination unit 381 reduces the degree of emotion held by the user. Rank in the rank.
[0289]
That is, the fact that the discourse range determination unit 340 determines that the second topic range is not related to the first topic range means that the current discourse range including the first morpheme information (second discourse range) Is different from the discourse range (the first discourse range) (the topic in context does not have cohesion; this is also referred to as “topic change”). 381 indicates that if the first morpheme information belonging to the second discourse range is included in the topic title (second morpheme information) associated with “low emotion level”, the first morpheme information is reduced by an emotion minus factor (topic change ( −)), And set a lower emotion level for the user (see FIGS. 26 and 27).
[0290]
Thereby, the topic change (-) indicates that the current discourse range is changed to another discourse range, and that the first morpheme information belonging to the changed discourse range is not interesting to the conversation control device 1. means.
[0291]
In this case, if the first morpheme information belonging to the second discourse range is included in the topic title (second morpheme information) associated with “high emotion level”, the emotion state determination unit 381 determines that the first morpheme information is It is also possible to determine that the emotion is a positive factor (change of topic (+)), and set the degree of emotion to the user to be higher.
[0292]
Thus, the topic change (+) means that the current discourse range is changed to another discourse range, and the first morpheme information belonging to the changed discourse range is an interesting content for the conversation control device 1. I do.
[0293]
On the other hand, when the discourse range determination unit 340 determines that the second discourse range has relevance to the first discourse range, the emotion state determination unit 381 ranks the degree of emotion held by the user at a higher rank. Attached.
[0294]
That is, the fact that the discourse range determination unit 340 determines that the second topic range has relevance to the first topic range means that the current discourse range including the first morpheme information (the second discourse range) is the previous one. Since it can be quasi-determined that they are substantially the same as the discourse range (the first discourse range) (the contextual topic has cohesion), the emotional state determination unit 381 sets the second discourse range If the first morpheme information belonging to is included in the topic title (second morpheme information) associated with “high emotion level”, it is determined that the first morpheme information is an emotion plus factor (cohesion factor (+)) Then, the degree of emotion held by the user is set to the higher one (see FIGS. 26 and 27).
[0295]
Thus, the unity factor (+) is that the current discourse range is substantially the same as the previous discourse range, and the first morpheme information belonging to the current discourse range is an interesting content for the conversation control device 1. Means
[0296]
In this case, if the first morpheme information belonging to the second discourse range is included in the topic title (second morpheme information) associated with “low emotion level”, the emotion state determination unit 381 determines that the first morpheme information is It is also possible to determine that the emotion is a negative factor (cohesion factor (-)) and set the degree of emotion to the user to be lower.
[0297]
Thus, the unity factor (-) is such that the current discourse range is substantially the same as the previous discourse range, but the first morpheme information belonging to the current discourse range is not interesting to the conversation control device 1. It means there is.
[0298]
In addition, when the morpheme constituting the discourse range is added to the first morpheme information by the abbreviation sentence complementing unit 350, the emotional state determination unit 381 ranks the degree of emotion held by the user to a higher rank. Can also be done.
[0299]
Specifically, the abbreviation sentence complementing unit 350 extracts a morpheme from each of the attributes (a subject case composed of a nominative case, a target case composed of a purpose case, etc.) constituting the first morphological information extracted by the sentence structure analyzing unit 430. Search for attributes not included. The abbreviation sentence complementing unit 350 adds, based on the retrieved attribute, a morpheme constituting the discourse range searched by the discourse range determination unit 340 to the attribute. When the morpheme constituting the discourse range is added to the first morpheme information by the abbreviation sentence complementing unit 350, the emotion state determination unit 381 ranks the degree of emotion held by the user at a higher rank.
[0300]
That is, in the abbreviation sentence complementing unit 350, the input information consisting of the first morpheme information is the abbreviation sentence (when the discourse range is added to the first morpheme information, the input information consisting of the first morpheme information before this morpheme is added) Means that the information is an abbreviated sentence) means that the user enters input information belonging to the current discourse range, assuming that it belongs to the current discourse range. Therefore, the input information input at this stage is likely to be an abbreviated sentence in which the morpheme comprising the current discourse range is omitted (for details, refer to the "abbreviated sentence in the first embodiment"). Complement section 350 ").
[0301]
Therefore, when the abbreviation sentence complementing unit 350 determines that the first morpheme information is an abbreviation, the emotional state determination unit 381 determines that the current discourse range is substantially the same as the previous discourse range. The first morpheme information is determined to be a cohesion factor having relevance to the previous discourse range. In this case, if the unity factor is the unity factor (+), the emotional state determination unit 381 sets the degree of emotion to the user to be higher, and if the unity factor is the unity factor (-), It is possible to set a lower emotion level for the user.
[0302]
Further, the emotional state determination unit 381 can also perform a step of ranking the degree of emotion held by the user based on a search result by the reflexive determination unit 320 or the parrot return determination unit 330. The reflexive determination unit 320 is a fixed form acquisition unit that collates the extracted first morpheme information with each of the fixed contents and searches for reflective element information including the first morpheme information from among the fixed contents.
[0303]
Specifically, when the reflexive determination unit 320 searches for the fixed content that matches the first morpheme information from among the fixed content, the emotional state determination unit 381 ranks the user with a lower degree of emotion. Rank.
[0304]
That is, the fact that the reflexive determination unit 320 has searched for the fixed content that matches the first morpheme information implies that the first morpheme information is an element (interruption factor) for interrupting the current topic. Therefore, the emotional state determination unit 381 determines that the first morpheme information is an emotion minus factor (interruption factor), and sets the emotion level to the user to be lower (see FIG. 26, FIG. 27). For example, if the user inputs "good morning" (regular content) which is completely unrelated to the topic during the conversation, "good morning" becomes a cause of interruption.
[0305]
In addition, the parrot return determining unit 330 determines that the current first morphological information extracted by the morphological extracting unit 410 is the past answer content extracted by the morphological extracting unit 410 (this past first morphological information is stored in the parrot returning element database 802). (Which is stored in the.).
[0306]
When the parrot return determination unit 330 determines that the current first morpheme information is included in the past answer content, the emotional state determination unit 381 determines that the current first morpheme information is included in the past answer content. It is simulated that the user is parrot about the past answer contents (the user is listening again to the answer contents), and the first morphological information is the interruption factor to interrupt the current topic Can be determined.
[0307]
In this case, since the current first morpheme information is an emotion minus factor (interruption factor), the emotion state determination unit 381 sets the degree of emotion to the user to be lower. (See FIGS. 26 and 27).
[0308]
Further, the parrot return determination unit 330 compares the current morpheme information extracted by the morpheme extraction unit 410 with the past first morpheme information, and determines that the current first morpheme information is included in the past first morpheme information. In this case, since the current first morpheme information is included in the past first morpheme information, the emotion state determination unit 381 determines that the user has the same input information as the past input information regardless of the current topic. Can be determined to be simply repeated. In this case, the emotion state determination unit 381 sets the degree of emotion to the user to be lower, because the input information repeatedly input is the cause of the interruption.
[0309]
If the reflexive determination unit 320 cannot search for the fixed content that matches the first morpheme information from each of the fixed content, the emotional state determination unit 381 ranks the emotion level held by the user at a higher rank. May be attached. If the parrot return determining unit 330 cannot search for past first morphological information or past answer content that matches the current first morphological information, the emotional state determining unit 381 ranks the user with a higher degree of emotion. May be ranked.
[0310]
Furthermore, when the input information specified by the utterance type determination unit 440 is a repulsion element such as a repulsion sentence, the emotion state determination unit 381 ranks the degree of emotion held by the user to a lower rank. Can also be done.
[0311]
That is, the fact that the input type of the input information input by the user is specified by the utterance type determination unit 440 to be a repulsive element means that the user and the conversation control device 1 are opposed. The emotional state determination unit 381 determines that the first morpheme information is an emotion minus factor (conflict factor), and determines that the degree of emotion held by the user is lower. It is set (see FIGS. 26 and 27).
[0312]
Next, when the topic search unit 360 does not search the second morpheme information including the first morpheme information from the second morpheme information, the understanding state determination unit 382 determines that the input information input by the user is difficult ( (Step S211). It is determined that the input information is difficult to understand, and the degree of understanding of the input information is ranked lower.
[0313]
Specifically, the fact that the second morpheme information including the first morpheme information is not searched for from the respective second morpheme information by the topic search unit 360 means that the first morpheme information is more difficult than the second morpheme information. Since the determination can be made in a simulated manner, the understanding state determination unit 382 determines that the first morpheme information is a cause of difficulty and sets the understanding level of the input information to a lower level.
[0314]
When the topic search unit 360 searches for the second morpheme information including the first morpheme information from each of the second morpheme information, the understanding state determination unit 382 easily converts the input information input by the user. May be determined, and the level of understanding of the input information may be ranked higher. When the first morpheme information is a factor that causes a topic change to a cohesion factor, the understanding state determination unit 382 may rank the understanding level of the input information to a higher rank.
[0315]
Next, when the input information specified by the utterance type determination unit 440 is a repulsion element (oppose; also referred to as a confrontation factor) such as a repulsion sentence, the confrontation state determination unit 383 determines the degree of confrontation with the user. A step of ranking a higher rank is performed (S212). If the input information specified by the utterance type determination unit 440 is not a repulsive element such as a repulsive sentence, the conflict state determination unit 383 performs a step of ranking the degree of conflict with the user to a lower rank. .
[0316]
Thereafter, the emotion state determination unit 381, the understanding state determination unit 382, or the conflict state determination unit 383 outputs the determined emotion degree, understanding degree, and conflict level to the output unit 600, and the output unit outputs the input emotion degree. Then, a step of displaying the degree of understanding and the degree of conflict is performed (S213).
[0317]
(Operation and Effect of Information Processing System and Information Processing Method)
According to the invention according to the present embodiment, the reflexive determination unit 320, the parrot return determination unit 330, or the topic search unit 360 collates the first morpheme information with each piece of the second morpheme information, and From the second morpheme information including the first morpheme information, the emotion state determination unit 381 determines the frequency of the second morpheme information including the first morpheme information from each second morpheme information. Since the ranking can be ranked as the degree of emotion held by the user according to the size, the emotion state determination unit 381 outputs, for example, the ranked size as the degree of emotion held by the user ( (For example, a screen, a voice, etc.), the conversation control device 1 can be used as a device for specifying the degree of emotion held by the user in a pseudo manner.
[0318]
Further, the developer who develops the information processing system can easily rank, for example, the degree of emotion based on the search history performed between the first morphological information and each of the second morphological information. It is not necessary to develop a complicated algorithm or a neural network for causing the information processing system to calculate the degree of emotion or the like held by the user, and as a result, the development time for developing this system can be reduced. .
[0319]
Further, the discourse range determination unit 340 has relevance between the first discourse range related to the first morpheme information searched first and the second discourse range related to the first morpheme information searched later. Is determined, and the emotional state determination unit 381 ranks the degree of emotional feeling held by the user based on the result determined by the discourse range determination unit 340. It is possible to rank the degree of emotion held by the user more appropriately than rank the degree of emotion held by the user based on the search result by matching the information with each second morpheme information it can.
[0320]
For example, if the second discourse range has no relationship with the first discourse range, the emotional state determination unit 381 has previously input the current input information (input from the user). Since it can be judged that the content is completely different from the input information, the user can quasi-determinate that the user has input inconsistency with respect to a certain topic, and It is possible to set a low emotion level (in a bad direction).
[0321]
On the other hand, if the second discourse range has relevance with the first discourse range, the emotion state determination unit 381 has previously input the current input information (input from the user). Since it can be determined that the input information has relevance, the user can quasi-determinate that the input is consistent with a certain topic, and The degree of emotion to be held can be set high (good direction).
[0322]
Further, when the morpheme of the discourse range is added to each attribute constituting the first morpheme information by the abbreviation sentence complementing unit 350, the emotion state determination unit 381 is an abbreviation of the input information composed of the first morpheme information. It can be determined that the user has input the input information on the premise of the previously searched discourse range.
[0323]
For this reason, when the first morpheme information including the input information is an abbreviation, the emotional state determination unit 381 may determine that the input information has been input based on the previously searched discourse range. Because it is possible, the user can falsely determine that the user is inputting consistency for a certain topic, and it is possible to set a high degree of emotion to the user (good direction) it can.
[0324]
Furthermore, the reflexive judgment unit 320 compares the first morpheme information with each of the fixed contents, searches for the fixed contents including the first morpheme information from each of the fixed contents, and the emotion state judgment unit 381 sets the Since the degree of emotion held by the user is ranked based on the search result, the emotional state determination unit 381 determines that the user has a certain topic when, for example, the standard content including the first morphological information is searched. Since it is possible to simulate that the input information for interrupting the input has been input, it is possible to rank the degree of emotion held by the user at a lower rank, and consequently to the user It is possible to rank the degree of emotions embraced more appropriately.
[0325]
On the other hand, when the reflexive determination unit 320 cannot search for the fixed content including the first morpheme information, the emotion state determination unit 381 inputs the input information for causing the user to interrupt a certain topic. However, since it can be falsely determined that the user has seriously answered the current topic, the degree of emotion held by the user can be ranked higher.
[0326]
Further, the utterance type determination unit 440 specifies the input type indicating the type of the input information, and if the specified input type is a repulsion element such as a repulsion sentence, the emotion state determination unit 381 notifies the user of The degree of emotion to be held can be ranked to a lower rank, and the degree of emotion to be held to the user can be ranked more appropriately.
[0327]
Furthermore, if the topic search unit 360 does not search for the second morpheme information including the first morpheme information, the understanding state determination unit 382 determines that the second morpheme information related to the first morpheme information is not stored in advance. Therefore, it can be pseudo-determined that the input information composed of the first morpheme information is more difficult than the sentence composed of the second morpheme information.
[0328]
For this reason, since the understanding state determination unit 382 cannot understand the input information composed of the first morphological information, the understanding state determining unit 382 quasi-determines that the user has input that the meaning is unknown for a certain topic. And the degree of understanding of the input information can be ranked lower.
[0329]
In addition, when the understanding state determination unit 382 can search the second morpheme information related to the first morpheme information by the topic search unit 360, the understanding state determination unit 382 determines that the user Therefore, it is possible to quasi-determine that the user has input meaningful information, and rank the input information with a high degree of understanding.
[0330]
Further, the developer who develops the conversation control device 1 can hierarchically construct the second morpheme information and the like for searching for the contents of the answer to the input information of the user using a language such as DKML. The conversation control device 1 can search the database for second morpheme information and the like related to the first morpheme information based on the first morpheme information corresponding to the input information of the user through a hierarchical procedure.
[0331]
That is, the reflexive determination unit 320, the parrot return determination unit 330, the discourse range determination unit 340, or the topic search unit 360 determines the hierarchy of the first morpheme information corresponding to the input information (for example, the second morpheme information stored in the database. Whether it is in the upper concept or in the lower concept), and the appropriate second morpheme information can be retrieved from each of the previously stored second morpheme information based on the determined hierarchy. .
[0332]
For this reason, the reflexive determination unit 320, the parrot return determination unit 330, the discourse range determination unit 340, or the topic search unit 360 uses the first morpheme information composed of the input information of the user and the second “all” stored in advance. The second morpheme information that is similar to the first morpheme information can be compared with the first morpheme information because it is sufficient to match each “specific” second morpheme information belonging to a specific hierarchy without matching each morpheme information. The search can be performed in a short time, and the results can be ranked in a short time according to the degree of emotion or the like held by the user based on the search result.
[0333]
Further, the parrot return determining unit 330 compares the current first morpheme information with the past answer contents, and when it is determined that the current first morphological information is included in the past answer contents, the emotion state determining unit 381. Can be quasi-determined that the user is parrot about the past answer contents (that the user is listening again to the answer contents).
[0334]
In this case, the emotional state determination unit 381 simulates that the user has input the input information for interrupting a certain topic because the user has performed a parrot on the past answer contents. Therefore, it is possible to rank the degree of emotion held by the user at a lower rank, and as a result, the degree of emotion held by the user can be ranked more appropriately.
[0335]
Lastly, the parrot return determination unit 330 compares the current first morpheme information with the past first morpheme information, and if the current first morpheme information is included in the past first morpheme information, determines the emotional state. The unit 381 can quasi-determine that the input information that the user has simply input in the past is what has been re-input irrespective of the answer content from the conversation control device 1.
[0336]
In this case, since the emotional state determination unit 381 has nothing to do with the content of the response from the conversation control device 1, the user has simply repeatedly input the same input information as the previous input information. The degree of emotion held by the user can be ranked lower, and as a result, the degree of emotion held by the user can be ranked more appropriately.
[0337]
[Third embodiment]
(Configuration of gaming machines)
The description of the third embodiment is as follows. FIG. 31 is a diagram showing the internal configuration of the gaming machine of the present embodiment. In this gaming machine, a plurality of nails are planted on the gaming board surface. In the above-mentioned gaming machine, a prize port for receiving a game ball for judging a winning state of discharging a predetermined number of game balls is provided on the game board surface. The gaming machine is a pachinko gaming machine that shifts to a winning state under predetermined conditions when a gaming ball ejected on the gaming board is inserted into a winning opening. However, the gaming machine of the present invention is not limited to a pachinko gaming machine.
[0338]
As shown in FIG. 31, the configuration of the gaming machine according to the present embodiment is substantially the same as the configuration of the conversation control device 1 according to the second embodiment, except for a winning opening 2100, a detecting unit 2200, and a first winning determining unit. 2300, an acquisition unit 371, and a first table database 501. Except for this difference, the configuration is the same as that of the first embodiment, the second embodiment, and each modified example, and the description of the configuration other than the difference will be omitted.
[0339]
In the second embodiment, the ranking unit 380 (emotion state determination unit 381, understanding state determination unit 382, confrontation state determination unit 383) determines based on input information (for example, voice information or the like) input by the user. The process of ranking the degree of emotions held by the user was explained.
[0340]
In the present embodiment, based on the size of the rank ranked by the ranking unit 380, the acquisition unit 371 generates a winning probability value (the description of the winning probability value will be described later) associated with the size of the rank. The first embodiment is different from the second embodiment in that a first winning determination unit (first determination unit) 2300 determines a winning state according to a winning probability value obtained and obtained by the obtaining unit 371. Here, the winning state in this embodiment means a state in which a large number of game balls are ejected. In addition, the first winning determination unit 2300 holds a winning probability value, and determines a winning state according to the held winning probability value.
[0341]
When a game ball is inserted into the winning opening 2100, the winning probability value indicating the probability that the first winning determination unit 2300 determines the winning state is associated with code information including a numerical value, and is stored in the first storage unit (the first storage unit). One table database 501) stores a plurality of the winning probability values.
[0342]
Specifically, the first table database 501 stores a plurality of first tables in which each piece of identification information is associated with winning information indicating a winning state or a non-winning state. In the first table, a winning probability value calculated based on the number of pieces of identification information and the number of pieces of identification information (hereinafter referred to as winning identification information) associated with the winning information indicating that the player is in a winning state, , And code information associated with the winning probability value.
[0343]
Thereby, “the first table is stored in the first table database 501” means “the winning probability value is stored in the first table database 501”. The first table database 501 stores code list information indicating a list of code information associated with each first table.
[0344]
Here, the identification information and the code information mean numerical values, for example. Specifically, in the present embodiment, as shown in FIG. 32, a first table in which code information, winning probability values, numerical values, and winning information are associated with each other is stored in the first table database 501.
[0345]
Specifically, as shown in FIG. 32, each of the code information (2) to (-2) includes, for example, a first table 2500a having a winning probability value of 1/150 and a first table 2500a having a winning probability value of 1/200. One table 2500b, a first table 2500c having a winning probability value of 1/250, a first table 2500d having a winning probability value of 1/300, and a first table 2500e having a winning probability value of 1/350 are associated with each other.
[0346]
The code list information 2600 includes code information 2, 1, 0, -1, and -2. These first tables are stored in the first table database 501. In the present embodiment, each piece of code information shown in FIG. 32 has the same size as the size of each rank (e (2), etc.) ranked by the emotional state determination unit 381. The size of each code information is associated with the size of each rank.
[0347]
Similarly, as shown in FIG. 33, each of the code information (1) to (-2) includes, for example, a first table 2510a having a winning probability value of 1/150 and a first table 2510b having a winning probability value of 1/200. A first table 2510c having a winning probability value of 1/250 and a first table 2510d having a winning probability value of 1/300 are associated with each other.
[0348]
These first tables are stored in the first table database 501. In addition, code information 1, 0, -1, and -2 are recorded in the code list information. In the present embodiment, each piece of code information shown in FIG. 33 has the same size as each rank (r (1), etc.) ranked by the understanding state determination unit 381. The size of each code information is associated with the size of each rank.
[0349]
As shown in FIG. 34, each of the code information (2) to (-2) includes, for example, a first table 2520a having a winning probability value of 1/150 and a first table 2520b having a winning probability value of 1/200. A first table 2520c having a winning probability value of 1/250, a first table 2520d having a winning probability value of 1/300, and a first table 2520e having a winning probability value of 1/350 are associated with each other. Further, code information 2, 1, 0, -1, -2 is recorded in the code list information.
[0350]
In the present embodiment, each code information shown in FIG. 34 has the same size as the size of each rank (such as o (2)) ranked by the conflict state determination unit 381. The size of each code information is associated with the size of each rank.
[0351]
The acquiring unit 371 collates the rank with each code information stored in advance in the first table database based on the rank ranked by the ranking unit 380, and obtains the above-mentioned rank from each code information. It is a code acquisition unit that acquires matching code information. Further, the acquisition unit 371 acquires a winning probability value (specifically, a first table) associated with the code information based on the obtained code information. Note that the ranking process is the same as the process described in the ranking section 380 of the second embodiment, and a detailed description thereof will be omitted here.
[0352]
Specifically, in the present embodiment, as illustrated in FIG. 32, the acquisition unit 371 to which the ranking signal is input from the emotion state determination unit 381, for example, receives the rank of the emotion degree corresponding to the input ranking signal ( 1) is compared with each code information (each code information recorded in the code list information) 2--2 stored in the first table database 501, and the rank of the degree of emotion is determined from each code information. Code information (1) that matches
[0353]
Similarly, in the present embodiment, as illustrated in FIG. 33, the acquisition unit 371 to which the ranking signal is input from the understanding state determination unit 382, for example, ranks of the understanding level corresponding to the input ranking signal (FIG. 33). 1) and each code information (each code information recorded in the code list information) 1 to -2 stored in the first table database 501 is collated. Then, the acquiring unit 371 acquires, from each piece of code information, code information (1) that matches the rank of the emotion degree.
[0354]
Similarly, in the present embodiment, as illustrated in FIG. 34, the acquisition unit 371 to which the ranking signal has been input from the conflict state determination unit 383, for example, has the rank of the conflict degree corresponding to the input ranking signal (FIG. 34). 1) is compared with each code information (each code information recorded in the code list information) 2-2 stored in the first table database 501. Then, the acquiring unit 371 acquires, from each piece of code information, code information (1) that matches the rank of the degree of opposition.
[0355]
The acquiring unit 371 having acquired the code information accesses the first winning determination unit 2300 and acquires the code information associated with the winning probability value held by the first winning determination unit 2300. Then, the acquisition unit 371 transmits the code information (hereinafter, first code information) that matches the rank and the code information (hereinafter, second code) associated with the winning probability value held by the first winning determination unit 2300. Information).
[0356]
Here, "the first winning determination unit 2300 holds the winning probability value" specifically means, for example, "the first winning determining unit 2300 holds a first table corresponding to the winning probability value". ”.
[0357]
If the first code information does not match the second code information, the obtaining unit 371 obtains a winning probability value associated with the first code information based on the obtained first code information. . Then, the acquiring unit 371 outputs the acquired winning probability value to the first winning determining unit 2300. In addition, even when the first winning determination unit 2300 does not hold the winning probability value, the acquiring unit 371 acquires the winning probability value associated with the first code information and sets the acquired winning probability value to the first winning information. Output to the winning determination unit 2300.
[0358]
Specifically, when the first code information and the second code information do not match, the obtaining unit 371 determines, based on the obtained first code information, a first table associated with the first code information. To get. Then, the obtaining unit 371 outputs the obtained first table to the first winning determination unit 2300. Note that, even when the first winning determination unit 2300 does not hold the first table, the obtaining unit 371 obtains the first table associated with the first code information and stores the obtained first table in the first table. Output to the winning determination unit 2300.
[0359]
On the other hand, when the first code information and the second code information match, the obtaining unit 371 does not obtain the winning probability value (specifically, the first table) associated with the first code information. In this case, the first winning determination unit 2300 already holds the winning probability value (specifically, the first table) corresponding to the first code information acquired by the acquiring unit 371.
[0360]
The detecting unit 2200 detects a game ball inserted into the winning opening 2100. The detection unit 2200 can be configured by, for example, an optical sensor. Specifically, the detecting unit 2200 detects that a game ball has been inserted into the winning opening 2100, and outputs a detection signal indicating the detection to the first winning determination unit 2300.
[0361]
The first winning determination unit 2300 determines whether or not a winning state is established according to the winning probability value output from the acquisition unit 371 based on the result detected by the detection unit 2200. Here, the winning state in this embodiment means a state in which a large number of game balls are ejected.
[0362]
Specifically, for example, the first winning determination unit 2300 determines whether or not the player is in a winning state based on the result detected by the detection unit 2200 and based on the first table output from the acquisition unit 371. I do. The detailed process of the first winning determination unit 2300 is as follows. The acquisition unit 371 sends the acquired first table to the first winning determination unit 2300. The first winning determination unit 2300 holds the first table. Then, a detection signal is output from the detection unit 2200 to the first winning determination unit 2300. The first winning determination unit 2300 counts each numerical value in the held first table while continuously changing it. For example, the first winning determination unit 2300 counts the numerical value in the first table corresponding to the winning probability value 1/200 shown in FIG. When the first winning determination unit 2300 has counted the numerical value up to 200, it counts again from 1.
[0363]
Then, the first winning determination unit 2300 selects one numerical value (one numerical value) counted in a predetermined time from the numerical values (1 to 200) counted continuously. Then, the first winning determination unit 2300 refers to the held first table and acquires the winning information associated with the selected one numerical value. Then, the first winning determination unit 2300 determines whether or not the player is in a winning state based on the obtained winning information.
[0364]
Here, the probability that the winning information associated with the one numerical value indicates the winning state is a winning probability value (for example, 1/200) corresponding to the first table. For this reason, "the first winning determination unit 2300 refers to the first table corresponding to the winning probability value (for example, 1/200) and, under the predetermined condition, sets a predetermined value among the numerical values (1 to 200). “Selecting one numerical value and determining the winning state based on the winning information corresponding to the predetermined numerical value” means that “the first winning determination unit 2300 determines the winning state based on the winning probability value (1/200). Is determined. "
[0365]
The first winning determination unit 2300 determines that the game is in a winning state when the acquired winning information indicates that the winning is achieved. Then, the first winning determination unit 2300 sends a winning signal indicating a winning state to a discharging unit (not shown). The discharging unit discharges a large number of game balls to the player based on the winning signal.
[0366]
On the other hand, if the acquired winning information indicates that the winning is not award, the first winning determining unit 2300 determines that the winning state is not established. Then, the first winning determination unit 2300 sends a non-winning signal indicating that the player is not in a winning state to the discharging unit. The discharging unit discharges, for example, a small number of game balls to the player based on the non-winning signal.
[0367]
(Gaming control method using a gaming machine)
The game control method using the gaming machine having the above configuration can be performed, for example, by the following procedure. The case where the first winning determination unit 2300 already holds the predetermined first table will be described as an example. In addition, also when the first winning determination unit 2300 refers to information other than the first table and determines the winning state according to the winning probability value, the game control method is performed in the same procedure as the following procedure. be able to.
[0368]
First, the gaming machine performs a winning determination process as described below. The detecting unit 2200 detects a game ball inserted into the winning opening 2100. The detection unit 2200 outputs a detection signal indicating that a game ball has been inserted to the first winning determination unit 2300. Based on the detection signal, the first winning determination unit 2300 refers to the held first table, selects a predetermined numerical value among the numerical values that have been continuously changed, and corresponds to the predetermined numerical value. Based on the winning information, it is determined whether or not a winning state is established.
[0369]
Hereinafter, “the first prize determination unit 2300 refers to the first table, selects a predetermined numerical value among the numerical values that have been continuously changed, and based on the prize information corresponding to the predetermined numerical value, wins. "Determining whether or not the player is in the state" is referred to as "the first winning determination unit 2300 refers to the first table to determine whether or not the player is in the winning state under predetermined conditions".
[0370]
When the first winning determination unit 2300 determines that the winning state has been achieved, the first winning determination unit 2300 sends a winning signal to the discharging unit. The discharging unit discharges a large number of game balls to the player based on the winning signal. On the other hand, when the first prize determination unit 2300 determines that the prize is not in a prize state, the first prize determination unit 2300 sends a non-prize signal to a discharge unit (not shown). The discharging unit discharges a small number of game balls to the player based on the non-winning signal.
[0371]
Then, in parallel with the above-described winning determination processing, a game control method using a gaming machine as described below is performed. FIG. 35 is a flowchart showing the procedure of the game control method according to the present embodiment.
[0372]
As shown in the figure, first, the input unit 100 acquires the utterance content input from the player (S301). Then, the morpheme extraction unit 410 specifies a character string constituting the utterance content based on the utterance content acquired by the input unit 100, and extracts each morpheme from the specified character string (S302, S303).
[0373]
After that, the phrase analysis unit 420 puts each morpheme into a phrase format based on each morpheme extracted by the morpheme extraction unit 410 (S304). In the present embodiment, each morpheme belonging to one phrase form is collectively referred to as first morpheme information. The processing of steps S301 to S304 is the same as the processing of S101 to S104 described in the first embodiment. Therefore, a detailed description of these processes will be omitted.
[0374]
Next, the ranking section 380 determines the degree of emotion held by the player based on the search result by the reflexive determination section 320, the parrot return determination section 330, the discourse range determination section 340, the abbreviation sentence complementation section 350, or the topic search section 360. And so on (S305). The process in step S305 is the same as the ranking process described in the information processing method according to the second embodiment, and a detailed description thereof will not be repeated.
[0375]
Then, based on the rank ranked by the ranking unit 380, the acquisition unit 371 collates the rank with each of the code information stored in advance, and among the code information, the code information that matches the rank. Is acquired (S306).
[0376]
Specifically, in the present embodiment, as illustrated in FIG. 32, the acquisition unit 371 to which the ranking signal is input from the emotion state determination unit 381, for example, receives the rank of the emotion degree corresponding to the input ranking signal ( 1) is compared with each code information (each code information recorded in the code list information) 2--2 stored in the first table database 501, and the rank of the degree of emotion is determined from each code information. Code information (1) that matches
[0377]
The acquiring unit 371 that has acquired the code information accesses the first winning determination unit 2300 and acquires the code information associated with the first table held by the first winning determination unit 2300.
[0378]
Then, the acquisition unit 371 compares the first code information that is the code information that matches the rank with the second code information that is the code information associated with the first table held by the first winning determination unit 2300. A comparison is made to determine whether they match (S307). If it is determined that they match, the process proceeds to the process of step S308. If it is determined that they do not match, the process proceeds to step S309.
[0379]
In step S308, the obtaining unit 371 does not obtain the first table associated with the first code information. In this case, the first winning determination unit 2300 already holds the first table corresponding to the first code information acquired by the acquisition unit 371. Then, the first winning determination unit 2300 determines a winning state under predetermined conditions with reference to the first table already held.
[0380]
In step S309, the acquiring unit 371 acquires a first table associated with the first code information based on the acquired first code information. Then, the obtaining unit 371 outputs the obtained first table to the first winning determination unit 2300. Note that, even when the first winning determination unit 2300 does not hold the first table, the obtaining unit 371 obtains the first table associated with the first code information and stores the obtained first table in the first table. Output to the winning determination unit 2300.
[0381]
The first winning determination unit 2300 refers to the first table output from the acquisition unit 371 based on the result detected by the detection unit 2200, and determines whether or not a winning state is established under predetermined conditions. Perform (S310).
[0382]
The specific processing of the first winning determination unit 2300 is, for example, as follows. The first table sent from the acquisition unit 371 is output to the first winning determination unit 2300. The first winning determination unit 2300 holds the first table. Then, a detection signal is output from the detection unit 2200 to the first winning determination unit 2300. The first winning determination unit 2300 counts each numerical value in the held first table while continuously changing it. Then, the first winning determination unit 2300 selects one numerical value counted in the predetermined time from the numerical values counted continuously. Then, the first winning determination unit 2300 refers to the held first table and acquires the winning information associated with the selected one numerical value.
[0383]
The first winning determination unit 2300 determines that the game is in a winning state when the acquired winning information indicates that the winning is achieved. On the other hand, if the acquired winning information indicates that the winning is not award, the first winning determining unit 2300 determines that the winning state is not established.
[0384]
Note that the acquisition unit 371 to which the ranking signal has been input from the understanding state determination unit 382 or the conflict state determination unit 383 performs the same processing as described above, and a detailed description thereof will be omitted.
[0385]
(Effect)
According to the invention of the present application, the acquisition unit (code acquisition unit) 371 collates the rank ranked by the ranking unit 380 with each piece of code information stored in advance, and among the pieces of code information, To obtain code information that matches.
[0386]
Then, the obtaining unit 371 obtains a winning probability value associated with the code information. Then, the first winning determination unit (first determination unit) 2300 determines the winning state according to the winning probability value acquired by the acquiring unit 371. Specifically, the obtaining unit 371 obtains the first table associated with the code information. Then, the winning determination unit 2300 refers to the first table acquired by the acquiring unit 371, selects a predetermined numerical value from each numerical value (each identification information), and sets the selected numerical value to the winning information corresponding to the selected predetermined numerical value. The winning state is determined based on the winning state.
[0387]
Therefore, if the rank ranked by the ranking section 380 is, for example, the degree of emotion held by the player, the first winning determination section 2300 determines the winning probability corresponding to the magnitude of the degree of emotion. The winning state can be determined according to the value. That is, the first winning determination unit 2300 refers to the first table corresponding to the magnitude of the degree of emotion and the like, selects a predetermined numerical value from each numerical value (each identification information), and sets the selected predetermined numerical value to the selected numerical value. The winning state can be determined based on the corresponding winning information.
[0388]
For example, if the currently ranked rank is the lowest, the first winning determination unit 2300 can determine the winning state according to the winning probability value associated with the lowest rank.
[0389]
Further, the ranking section 380 ranks various ranks according to the content of the utterance of the player. For example, a high rank is associated with a high winning probability value (specifically, a first table of high winning probability values), and a low rank is associated with a low winning probability value (specifically, a low winning probability value). If the first table of the probability values is associated, the following effects can be obtained.
[0390]
That is, depending on the content of the utterance of the player, the first winning determination unit 2300 may determine the winning state according to a high winning probability value, or may determine the winning state according to a low winning probability value. . Therefore, depending on the utterance content of the player, the gaming machine may be likely to be in the winning state, or may be difficult to be in the winning state. Therefore, the player plays the game without predicting when the winning state is likely to occur and when the winning state is unlikely to occur. This allows the player to play the game with thrill and excitement during the game.
[0391]
(First modification example)
FIG. 36 is a diagram illustrating a configuration of a gaming machine according to the present modification. The gaming machine according to the third embodiment is different from the gaming machine according to the third embodiment in that the gaming machine according to the third embodiment includes a second table database 502, a rank determining unit (second determining unit) 2400, and a different function of a first winning determination unit 2300. Machine. In the configuration of the present modified example, the description of the same configuration as the configuration of the third embodiment is omitted.
[0392]
The second database 502 stores a second table. In the second table, each numerical value is associated with winning information indicating whether or not the player is in a winning state. Then, the winning probability value of the second table is higher than the highest winning probability value among the winning probability values of all the first tables stored in the first database 501. Here, the winning probability value of the table is calculated based on the number of each numerical value in the table and the number of winning identification information in the table. The second table may be stored in the first database 501 without providing the second database 502.
[0393]
When the first prize determining unit 2300 determines that the game is in the winning state, the rank determining unit 2400 determines whether the current rank ranked by the ranking unit 380 is the highest rank. The ranking unit 380 here is, for example, an emotion state determination unit 381 and an understanding state determination unit 382. The rank is, for example, a rank of the degree of emotion or a rank of the degree of understanding.
[0394]
The rank determining unit 2400 holds list information of ranks ranked by the ranking unit 380. In this list information, for example, rank (-2) to rank (2) are recorded. The ranking unit 380 holds the current rank that has been ranked.
[0395]
The specific processing of the rank determination unit 2400 is as follows. First, when the first winning determination unit 2300 determines that the player is in the winning state, the first winning determination unit 2300 outputs a winning signal indicating that the player is in the winning state to the rank determining unit 2400. The rank determination unit 2400 acquires the current rank from the ranking unit based on the winning signal. Then, the rank determining unit 2400 refers to the list information and determines whether or not the current rank is the highest rank.
[0396]
When determining that the rank is the highest rank, the rank determination unit 2400 sends a signal indicating that to the acquisition unit 371. The acquisition unit 371 acquires the second table from the second database 502 based on the signal indicating the above. Then, the acquisition unit 371 sends the acquired second table to the first winning determination unit 2300.
[0397]
On the other hand, when determining that the rank is not the highest rank, the rank determination unit 2400 sends a signal indicating that to the acquisition unit 371. The acquiring unit 371 does not acquire the second table from the second database 502 based on the signal indicating the above. In this case, the second table is not sent to the first winning determination unit 2300.
[0398]
The first winning determination unit 2300 holds the second table when the rank determination unit 2400 determines that the current rank is the highest rank. Then, the first winning determination unit 2300 that has obtained the detection signal from the detection unit 2200 refers to the second table, selects a predetermined numerical value among the numerical values that have been continuously changed, and corresponds to the predetermined numerical value. It is determined whether or not the player is in a winning state based on the winning information.
[0399]
According to this modification, the rank determining unit (second determining unit) 2400 determines whether the current rank ranked by the ranking unit 380 is the highest. The second table is stored in the second table database 502. The winning probability value of the second table is higher than the highest winning probability value among the winning probability values of the first tables stored in the first table database 501.
[0400]
Then, when the rank determining unit 2400 determines that the current rank is the highest, the first winning determination unit 2300 refers to the second table and selects a predetermined numerical value among the numerical values that are continuously changed. Then, it is determined whether or not a winning state is established based on the winning information corresponding to the predetermined numerical value.
[0401]
The ranking unit 380 may rank the current rank to the highest rank based on the content spoken by the player. In such a case, the first winning determination unit 2300 determines a winning state according to a very high winning probability value. As a result, in the present modification, the gaming machine may be very likely to be in a winning state depending on the utterance content of the player.
[0402]
Therefore, according to the present modified example, in addition to the effect of the third embodiment, the player can play a game while having the expectation that the number of times a large number of game balls are discharged may increase. it can.
[0403]
(Second modification example)
In the first modification, when the rank determination unit 2400 determines that the rank is not the highest rank, the second table is not sent to the first winning determination unit 2300. However, in the present modification, the following may be performed. .
[0404]
If the rank determination unit 2400 determines that the rank is not the highest rank, it sends a signal indicating that to the second winning determination unit (not shown).
[0405]
The second winning determination unit holds a correspondence table in which each numerical value is associated with the first information or the second information. The first information is information indicating that the first winning determination unit 2300 instructs to determine a winning state based on the second table. The second information is information indicating that it is instructed to determine a winning state based on the first table currently held by the first winning determination unit 2300.
[0406]
For example, in the correspondence table, the numerical information (1) is associated with the first information, and the numerical information (2 to 10) is associated with the second information.
[0407]
The second winning determination unit counts each numerical value in the held correspondence table while continuously changing it based on the signal indicating the above. Then, the second winning determination unit selects one numerical value counted in a predetermined time from the numerical values counted continuously. Then, the second winning determination unit refers to the held correspondence table to acquire the first information or the second information associated with the selected one numerical value.
[0408]
Then, when acquiring the first information, the second winning determination unit sends to the obtaining unit 371 an instruction to send the second table to the first winning determination unit 2300. The acquiring unit 371 acquires a second table from the second database 502 based on the command. Then, the acquisition unit 371 sends the acquired second table to the first winning determination unit 2300. The first winning determination unit 2300 holds the second table. Then, the first winning determination unit 2300 that has obtained the detection signal from the detection unit 2200 refers to the second table, selects a predetermined numerical value among the numerical values that have been continuously changed, and corresponds to the predetermined numerical value. It is determined whether or not the player is in a winning state based on the winning information.
[0409]
On the other hand, when acquiring the second information, the second winning determination unit 2300 sends a command to the obtaining unit 371 not to send the second table to the first winning determination unit 2300. The acquiring unit 371 does not acquire the second table from the second database based on the command. In this case, the second table is not sent to the first winning determination unit 2300.
[0410]
According to this modification, even when the ranking unit 380 does not rank the current rank as the highest rank, the first winning determination unit 2300 may determine the winning state according to a very high winning probability value. . Therefore, according to the present modified example, compared with the first modified example, the player plays the game while having a stronger expectation that a large number of game balls may be ejected more frequently. Can be.
[0411]
In the first modified example and the second modified example, when the first winning determination unit 2300 changes the rank ranked by the ranking unit after holding the second table, the third embodiment will be described. As described above, the first table corresponding to the rank is sent to the first winning determination unit 2300. The first winning determination unit 2300 holds the sent first table and refers to the first table to determine a winning state under predetermined conditions.
[0412]
In addition, the gaming machine can output the magnitude ranked based on the search history performed between the first morpheme information and each piece of the second morpheme information as an emotion degree or the like. Therefore, the developer who develops the gaming machine does not need to develop a complicated algorithm, a neural network, or the like for causing the gaming machine to calculate the degree of emotion or the like held by the player. As a result, development time for developing a device that achieves the present invention is reduced.
[0413]
In addition, the second morpheme information including the first morpheme information (including the discourse range, the fixed content or the answer content, etc .; hereinafter, abbreviated as “second morpheme information, etc.”) means that the second morpheme information is the first morpheme information. This means not only the case where the information is included as it is, but also the case where the second morpheme information and the like include at least one morpheme constituting the first morpheme information.
[0414]
Further, the contents described in the gaming machine and the game control method of the third embodiment and its modified example are, like the first embodiment, the second embodiment and its modified example, a general-purpose computer such as a personal computer. It can be realized by executing a dedicated program for using a programming language. Further, the above-described program can be recorded on a recording medium, similarly to the first embodiment, the second embodiment, and modifications thereof.
[0415]
【The invention's effect】
As described above, according to the present invention, based on input information input from a player, a previously created answer content or the like associated with semantic content grasped from this input information is searched, and Ranking is performed according to the frequency. Then, according to the present invention, the ranked size can be reflected on the winning probability value as the degree of emotion for the player or the like. As a result, depending on the content of the utterance of the player, the first determination unit may determine the winning state according to a high winning probability value, or may determine the winning state according to a low winning probability value.
[0416]
Therefore, depending on the utterance content of the player, the gaming machine may be likely to be in the winning state, or may be difficult to be in the winning state. Thereby, the player can play the game with a feeling of thrill and excitement.
[Brief description of the drawings]
FIG. 1 is a block diagram illustrating a schematic configuration of a conversation control device according to a first embodiment.
FIG. 2 is a block diagram illustrating an internal structure of a conversation control unit and a sentence analysis unit according to the first embodiment.
FIG. 3 is a diagram illustrating the content of each morpheme extracted by a morpheme extraction unit according to the first embodiment.
FIG. 4 is a diagram showing the contents of each phrase extracted by a phrase analysis unit in the first embodiment.
FIG. 5 is a diagram illustrating contents of “case” specified by a sentence structure analysis unit according to the first embodiment.
FIG. 6 is a diagram illustrating “utterance sentence type” specified by an utterance type determination unit according to the first embodiment.
FIG. 7 is a diagram showing the contents of each dictionary stored in the utterance type database in the first embodiment.
FIG. 8 is a diagram showing contents of a hierarchical structure constructed inside a conversation database in the first embodiment.
FIG. 9 is a diagram showing a detailed relationship of a hierarchical structure constructed inside a conversation database in the first embodiment.
FIG. 10 is a diagram showing the contents of a “topic title” constructed inside a conversation database in the first embodiment.
FIG. 11 is a diagram showing the contents of “type of answer sentence” associated with “topic title” constructed inside the conversation database in the first embodiment.
FIG. 12 is a diagram showing contents of “topic title” and “answer sentence” belonging to a “discussion range” constructed inside a conversation database in the first embodiment.
FIG. 13 is a diagram illustrating contents of reflection element information stored in a reflection element database according to the first embodiment.
FIG. 14 is a diagram showing parrot return elements stored in a parrot return element database and the contents of morphemes of the parrot return elements in the first embodiment.
FIG. 15 is a flowchart illustrating a procedure of a conversation control method according to the first embodiment.
FIG. 16 is a diagram showing utterance contents arranged by a morpheme extraction unit in the first modification.
FIG. 17 is a diagram illustrating an internal configuration of a topic search unit according to a second modification.
FIG. 18 is a diagram illustrating a manner in which the ratio calculation unit in the second modification checks each morpheme belonging to “case configuration” and each “topic title” for each “topic title”.
FIG. 19 is a diagram illustrating a manner in which the ratio calculation unit in the second modification checks each morpheme belonging to “each component” and each morpheme belonging to “topic title” for each “case”.
FIG. 20 is a diagram illustrating a schematic configuration of a conversation control system according to a third modification.
FIG. 21 is a diagram illustrating an internal configuration of a topic search unit in a sixth modification.
FIG. 22 is a diagram illustrating a manner in which a topic search unit in the sixth modification example compares first morpheme information with second morpheme information or an answer sentence.
FIG. 23 is a diagram illustrating a recording medium that stores a program according to the present embodiment.
FIG. 24 is a block diagram illustrating an internal structure of a conversation control unit and a sentence analysis unit according to the second embodiment.
FIG. 25 is a diagram showing the contents of a “discount event table” stored in a discourse event database according to the second embodiment.
FIG. 26 is a diagram showing a relationship between “topic change” and “cohesion factor” in the second embodiment.
FIG. 27 is a diagram illustrating a rank of an emotion degree determined by an emotion state determination unit according to the second embodiment.
FIG. 28 is a diagram illustrating a rank of an understanding level determined by an understanding state determination unit according to the second embodiment.
FIG. 29 is a diagram illustrating a rank of a degree of conflict determined by a conflict state determination unit according to the second embodiment.
FIG. 30 is a flowchart showing a procedure of a ranking method in the second embodiment.
FIG. 31 is a view showing the internal configuration of the gaming machine of the third embodiment.
FIG. 32 is a diagram illustrating an example of contents stored in a first table database according to the third embodiment.
FIG. 33 is a diagram illustrating an example of contents stored in a first table database according to the third embodiment.
FIG. 34 is a diagram illustrating an example of contents stored in a first table database according to the third embodiment.
FIG. 35 is a flowchart illustrating a game control method according to the third embodiment.
FIG. 36 is a view showing the internal configuration of a gaming machine according to a first modification of the third embodiment.
[Explanation of symbols]
DESCRIPTION OF SYMBOLS 1 ... Conversation control device, 100 ... Input part, 200 ... Speech recognition part, 300 ... Conversation control part, 310 ... Management part, 320 ... Reflective judgment part, 321 ... Rate calculation part, 322 ... Selection part, 330 ... Parrot return judgment Section, 340: discourse range determination section, 350: abbreviation sentence complement section, 360: topic search section, 361 ... deletion section, 362 ... discourse addition section, 370 ... answer sentence search section, 371 ... acquisition section, 380 ... ranking section , 381: emotion state determination unit, 382: understanding state determination unit, 383: conflict state determination unit, 400: sentence analysis unit, 410: morpheme extraction unit, 420: phrase analysis unit, 430: sentence structure analysis unit, 440: utterance Type determination unit, 450: morpheme database, 460: utterance type database, 500: conversation database, 501: first table database, 502: second table database, 60 ... output unit, 700 ... voice recognition dictionary storage unit, 800 ... communication unit, 801 ... reflection element database, 802 ... parrot return element database, 900 ... communication unit, 1000 ... communication network, 1100 ... hard disk, 1200 ... flexible disk, 1300 ... Compact disc, 1400 IC chip, 1500 cassette tape, 2100 winning opening, 2200 detecting section, 2300 first winning determining section, 2400 rank determining section 2500a to 2520e first table.

Claims (15)

A gaming machine having first determination means for determining the winning state when the gaming ball is inserted into a winning port for receiving a gaming ball for determining a winning state for discharging a predetermined number of gaming balls,
When the gaming ball is inserted into the winning opening, a winning probability value indicating a probability that the first determination means determines the winning state is associated with code information including a numerical value, the winning probability value A plurality of first storage means for storing in advance;
A morpheme extracting unit configured to extract at least one morpheme constituting a minimum unit of the character string as first morpheme information based on a character string of input information input from a player;
Morphological storage means for storing a plurality of second morphological information indicating a predetermined morpheme in advance,
The first morpheme information extracted by the morpheme extraction unit is compared with each of the second morpheme information, and the second morpheme information including the first morpheme information is searched from the second morpheme information. A first search means;
Based on the search result searched by the first search means, the second morpheme information including the first morpheme information is ranked from the second morpheme information in accordance with the magnitude of the search frequency. Means for ranking,
A code acquisition unit that collates the rank with each of the code information based on the rank ranked by the ranking unit, and obtains, from each of the code information, code information that matches the rank. ,
A gaming machine, wherein the first determining means determines the winning state according to a winning probability value corresponding to the code information acquired by the code acquiring means. The first determination means is a first table in which when the gaming ball is inserted into the winning opening, each identification information including each numerical value and the winning information indicating whether or not the winning state is established, are associated with each other. With reference to, select predetermined identification information from each identification information, based on the winning information corresponding to the predetermined identification information, determine the winning state,
In the first table, the number of each piece of identification information, the winning probability value calculated based on the number of winning identification information is identification information associated with the winning information indicating a winning state, The code information associated with the winning probability value is associated with, and the first storage unit stores a plurality of the first tables in advance,
The first determination unit refers to a first table corresponding to the code information acquired by the code acquisition unit, selects predetermined identification information among the pieces of identification information, and corresponds to the selected predetermined identification information. The gaming machine according to claim 1, wherein the winning state is determined based on winning information. The gaming machine according to claim 2, wherein the ranking unit outputs the ranked size as a degree of emotion for the player. The method according to claim 2, wherein the ranking unit ranks a low rank when the search frequency is low, and ranks a high rank when the search frequency is high. The described gaming machine. When the first determination unit determines that the winning state, the current rank ranked by the ranking unit, the second determination unit to determine whether the highest,
The winning probability value calculated based on the number of each piece of the identifying information in the second table in which each piece of the identifying information is associated with the winning information, and the number of the winning identifying information in the second table is And a second storage means for storing the second table in advance, which is higher than the highest winning probability value among the winning probability values associated with each first table,
When the current rank is determined to be the highest by the second determination means, the first determination means refers to the second table and selects predetermined identification information from each piece of identification information. The gaming machine according to claim 4, wherein the winning state is determined based on winning information corresponding to the predetermined identification information. A game control method for a gaming machine, comprising: judging means for judging the winning state when the gaming ball is inserted into a winning port for accepting the game ball for judging a winning state for discharging a predetermined number of game balls. hand,
When the gaming ball is inserted into the winning opening, a winning probability value indicating a probability that the determining means determines the winning state is associated with code information including a numerical value, and the winning probability value is a plurality of Storing in a first storage means;
Extracting at least one morpheme constituting a minimum unit of the character string as first morpheme information based on the character string of the input information input from the player;
Storing a plurality of second morpheme information indicating a predetermined morpheme in advance in a morpheme storage unit;
Collating the extracted first morpheme information and the respective second morpheme information, and searching for the second morpheme information including the first morpheme information from the respective second morpheme information,
Based on the searched search result, from the respective second morpheme information, ranking the second morpheme information including the first morpheme information according to the magnitude of the frequency of being searched,
Based on the ranked rank, collating the rank and each of the code information, from among the code information, obtaining code information that matches the rank,
A step of the determining means determining the winning state according to the winning probability value corresponding to the acquired code information. When the gaming ball is inserted into the winning opening, the determination unit refers to the first table in which each piece of identification information including each numerical value and the winning information indicating whether or not the winning state is established are associated with each other. Selecting predetermined identification information from among the identification information, and determining the winning state based on winning information corresponding to the predetermined identification information;
In the first table, the number of each piece of identification information, the winning probability value calculated based on the number of winning identification information is identification information associated with the winning information indicating a winning state, The code information associated with the winning probability value is associated with, and a plurality of the first tables are stored in the first storage means in advance;
With reference to the first table corresponding to the acquired code information, the determination means selects predetermined identification information from each piece of identification information, and based on the winning information corresponding to the predetermined identification information, determines 7. The game control method according to claim 6, further comprising: determining a state. The game control method according to claim 7, wherein the ranked size is set as an emotion level of the player. 9. The game control method according to claim 7, wherein when the search frequency is low, the rank is ranked low, and when the search frequency is high, the rank is ranked high. A step of determining whether or not the ranked current rank is the highest when the determination unit determines that the winning state is established;
The winning probability value calculated based on the number of each piece of the identifying information in the second table in which each piece of the identifying information is associated with the winning information, and the number of the winning identifying information in the second table is Storing the second table in the second storage means in advance, which is higher than the highest winning probability value among the winning probability values associated with each first table,
When it is determined that the current rank is the highest, the determination unit refers to the second table, selects predetermined identification information from each piece of identification information, and corresponds to the predetermined identification information. 10. The game control method according to claim 9, further comprising the step of determining the winning state based on winning information. A control program for a gaming machine, comprising: a determination unit configured to determine a winning state when the gaming ball is inserted into a winning port for receiving a gaming ball for determining a winning state for discharging a predetermined number of gaming balls. On the computer,
When the gaming ball is inserted into the winning opening, a winning probability value indicating a probability that the determining means determines the winning state is associated with code information including a numerical value, and the winning probability value is a plurality of Storing in a first storage means;
Extracting at least one morpheme constituting a minimum unit of the character string as first morpheme information based on the character string of the input information input from the player;
Storing a plurality of second morpheme information indicating a predetermined morpheme in advance in a morpheme storage unit;
Collating the extracted first morpheme information and the respective second morpheme information, and searching for the second morpheme information including the first morpheme information from the respective second morpheme information,
Based on the searched search result, from the respective second morpheme information, ranking the second morpheme information including the first morpheme information according to the magnitude of the frequency of being searched,
Based on the ranked rank, collating the rank and each of the code information, from among the code information, obtaining code information that matches the rank,
A determination program for determining a winning state according to a winning probability value corresponding to the acquired code information. When the gaming ball is inserted into the winning opening, the determination unit refers to the first table in which each piece of identification information including each numerical value and the winning information indicating whether or not the winning state is established are associated with each other. Selecting predetermined identification information from among the identification information, and determining the winning state based on winning information corresponding to the predetermined identification information;
In the first table, the number of each piece of identification information, the winning probability value calculated based on the number of winning identification information is identification information associated with the winning information indicating a winning state, The code information associated with the winning probability value is associated with, and a plurality of the first tables are stored in the first storage means in advance;
With reference to the first table corresponding to the acquired code information, the determination means selects predetermined identification information from each piece of identification information, and based on the winning information corresponding to the predetermined identification information, determines The control program according to claim 11, wherein the control program is configured to execute processing having a step of determining a state. 13. The control program according to claim 12, wherein the ranked size is set as an emotion level of the player. 14. The control program according to claim 12, wherein when the search frequency is low, the rank is ranked low, and when the search frequency is high, the rank is ranked high. A step of determining whether or not the ranked current rank is the highest when the determination unit determines that the winning state is established;
The winning probability value calculated based on the number of each piece of the identifying information in the second table in which each piece of the identifying information is associated with the winning information, and the number of the winning identifying information in the second table is Storing the second table in the second storage means in advance, which is higher than the highest winning probability value among the winning probability values associated with each first table,
When it is determined that the current rank is the highest, the determination unit refers to the second table, selects predetermined identification information from each piece of identification information, and corresponds to the predetermined identification information. 15. The control program according to claim 14, for executing a process having a step of judging a winning state based on winning information.

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