JP4038399B2 - Face image display device, face image display method and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To retrieve previously generated response contents associated with meaning contents grasped from input information on the basis of input information on a sound or the like inputted from a user, to rank the contents in accordance with the frequency of retrieval and to reflect a ranked size on a facial picture as the degree of feeling about the user. <P>SOLUTION: The device is provided with: a ranking part 380 for ranking in accordance with the frequency that second morpheme information including first morpheme information is retrieved from individual pieces of second morpheme information on the basis of a retrieval result retrieved by a subject retrieval part 360; and a facial picture acquisition part 371 collating ranks with respective codes which are previously stored on the basis of the ranking made by the ranking part 380, acquiring the code matching the rank from the individual codes and displaying the facial picture corresponding to the code on a screen according to the acquired code. <P>COPYRIGHT: (C)2004,JPO

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention ranks a feeling level or the like held for a user at a predetermined stage based on input information such as voice input from the user, and determines a specific face according to the ranked size. The present invention relates to a face image display device that displays an image on a screen, a face image display method, and a program.
[0002]
[Prior art]
Conventionally, when a user speaks to a robot, the robot changes the facial expression displayed on the display unit using the display unit provided on the robot's head, Can express emotions to a certain user. As a result, the face image displayed on the display unit in the robot changes as the user speaks, so that the user can feel as if he / she is speaking with another user. be able to.
[0003]
[Problems to be solved by the invention]
However, since the face image displayed on a conventional robot or the like is arbitrarily displayed in response to the utterance content from the user, the user can mechanically display the face image on the screen. I couldn't wipe out the perception that it was made, and I couldn't see it as a realistic expression of humans.
[0004]
On the other hand, if the face image displayed on the display unit changes according to the utterance content from the user, the user can change the displayed face image in various ways according to the utterance content. The changing face image can be seen as a facial expression that is closer to a human being, and the user can also feel like having a conversation with other users.
[0005]
However, even if the face image displayed on the display section changes based on the utterance content from the user, the facial expression of the face image simply changes based on a specific keyword included in the utterance content. Because there is, it does not reflect the degree of emotion that the robot has to the user in the facial expression. For this reason, the user has not been able to experience a realistic feeling as if the user is having a conversation with another user.
[0006]
Therefore, the present invention has been made in view of the above points, and based on input information such as voice input from the user, it has been created in advance that is associated with the meaning content grasped from this input information. Search the contents of answers, etc., rank them according to the frequency of this search, and reflect this rank in the facial expression as the degree of emotion to the user. An object of the present invention is to provide a face image display device, a face image display method, and a program capable of giving a realistic feeling as if a user is having a conversation with another user.
[0007]
[Means for Solving the Problems]
The invention according to the present application has been made in order to solve the above-described problem, and a face image formed of a face image of a human being, an animal, or the like is associated with a code such as a character or a numerical value, respectively. A plurality of images are stored in advance, a character string indicating input information is specified based on input information such as voice input from a user, and at least one of the minimum units of the character string is configured based on the specified character string One morpheme is extracted as first morpheme information, a plurality of second morpheme information indicating a morpheme composed of one character, a plurality of character strings, or a combination thereof is stored in advance, and the extracted first morpheme information and each second morpheme Information is collated, second morpheme information including the first morpheme information is retrieved from each second morpheme information, and the first morpheme is retrieved from each second morpheme information based on the retrieved search result. Second form with information The element information is ranked according to the frequency of the search, and the rank is compared with each pre-stored code based on the ranked rank, and the rank matches with the rank. A code is acquired, and based on the acquired code, a face image associated with the code is displayed on the screen.
[0008]
In addition, when the said search frequency is low, it ranks to a low rank, and when a search frequency is high, it is preferable to rank to a high rank. Moreover, it is preferable to output the rank of the ranked rank as the degree of understanding of the input information, or to output the rank of the ranked rank as the degree of emotion or confrontation held for the user.
[0009]
According to the invention according to the present application, the face image display device ranks according to the frequency with which the second morpheme information including the first morpheme information is searched from the second morpheme information. The rank is compared with each code stored in advance, and a code matching the rank is obtained from each code, and the face image associated with the code is displayed on the screen based on the obtained code. Since it can be displayed, the face image display device corresponds to the magnitude of the emotion level, etc., if the rank ranked with reference to the search result is the emotion level held for the user. The face image to be displayed can be displayed on the screen.
[0010]
That is, the face image display device can switch the face image to be displayed on the screen according to the degree of emotion to the user. For example, if the currently ranked rank is the lowest, the face image is displayed at the lowest rank. Associated face images (expressions consisting of angry faces) can be displayed on the screen. Also, as a result, the facial expression displayed on the screen changes according to the size of the rank, so that the user is talking while listening to other people's complexions. You can taste a real sense.
[0011]
Furthermore, since the face image display device can output the ranked size as the emotion degree based on the search history performed between the first morpheme information and each second morpheme information, The developer who develops the image display device does not need to develop a complicated algorithm or neural network for causing the face image display device to calculate the degree of emotion held by the user. Development time for developing a device to achieve can be shortened.
[0012]
The second morpheme information including the first morpheme information includes not only the case where the second morpheme information includes the first morpheme information as it is, but the second morpheme information includes at least one morpheme constituting the first morpheme information. It also means a case.
[0013]
DETAILED DESCRIPTION OF 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 apparatus 1 (ranked apparatus) according to the present embodiment.
[0014]
As shown in the figure, 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. Part 700.
[0015]
In the present embodiment, for convenience of explanation, the description is limited to the user's utterance content (this utterance content is a kind of input information), but is not limited to the user's utterance content, and the keyboard. The input information may be input from the above. Therefore, the “utterance content” shown below can be described by replacing “utterance content” with “input information”.
[0016]
Similarly, in the following description, for convenience of explanation, the description will be limited to the “spoken sentence type” (speech type), but is not limited to this “spoken sentence type”, and input from a keyboard or the like. It may be an “input type” indicating the type of input information. Accordingly, the following “speech sentence type” (speech type) can be described by replacing “speech type” with “input type”.
[0017]
The input unit 100 is an acquisition unit that acquires input information from a user. In the present embodiment, a microphone, a keyboard, and the like are used. 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.
[0018]
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 input information based on the input information (other than voice) input, and outputs the specified character string to the conversation control unit 300 as a character string signal. Further, the input unit 100 that has acquired the utterance content from the user (the utterance content is composed of voice and is a kind of input information) with a microphone or the like, the voice constituting the acquired utterance content is a voice signal. To the voice recognition unit 200.
[0019]
The voice recognition unit 200 is a character recognition unit that identifies 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 a speech signal is input from the input unit 100 analyzes the input speech signal, and a character string corresponding to the analyzed speech signal is stored 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 speech recognition dictionary storage unit 700 stores a dictionary corresponding to standard speech signals.
[0020]
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 are included. A sentence structure analysis unit 430, an utterance type determination unit 440, a morpheme database 450, and an utterance type database 460.
[0021]
The morpheme extraction unit 410 is a morpheme extraction unit that extracts each morpheme constituting a minimum unit of a character string as first morpheme information based on the character string specified by the input unit 100 or the speech recognition unit 200.
[0022]
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 this embodiment, the morpheme means the minimum unit of the word structure represented in the character string. As the minimum unit of the word structure, as shown in FIG. 3, for example, parts of speech such as nouns, adjectives and verbs can be cited. In the present embodiment, each morpheme is expressed as m1, m2,.
[0023]
That is, the morpheme extraction unit 410 collates a character string corresponding to the input character string signal with a morpheme group such as nouns, adjectives, and verbs stored in advance in the morpheme database 450, and the morpheme is extracted 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.
[0024]
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 morphemes corresponding to the input extraction signal to combine them into a phrase format.
[0025]
Here, in this embodiment, the phrase format is a sentence in which the independent grammar or one or more attached words are attached to the independent grammar in the Japanese grammar, or a character string that does not destroy the meaning of the Japanese grammar. Means a sentence that is separated as finely as possible. This clause is expressed as p1, p2,... Pk in this embodiment.
[0026]
That is, as shown in FIG. 4, the phrase analysis unit 420 extracts and extracts the dependency elements (for example, gahahahahaha ...) of each morpheme based on each morpheme corresponding to the input extraction signal. Each morpheme is grouped into each clause based on the dependency element.
[0027]
The phrase analysis unit 420 that collects each morpheme into each phrase includes a sentence structure analysis unit 430 and an utterance type determination unit 440 using sentence pattern information including each phrase that combines each morpheme and each morpheme constituting each phrase as a sentence pattern signal. Output to.
[0028]
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 case and target case. Specifically, the sentence structure analysis unit 430, to which the sentence pattern signal is input from the phrase analysis unit 420, determines each morpheme included in the phrase based on each morpheme corresponding to the input sentence pattern signal and the phrase composed of each morpheme. Determine the “case composition”.
[0029]
Here, the “case structure” means a case (attribute) indicating a substantial concept in the clause. In the present embodiment, for example, a subject (subject) that represents a subject / subject, Object meaning (object case), action meaning motion, time meaning time (thing consisting of mood, tense, aspect, etc.), location meaning place, and the like. In this embodiment, each morpheme associated with the “case” (case configuration) of the three elements of the subject, the object, and the action is used as the first morpheme information.
[0030]
That is, as shown in FIG. 5, for example, when the dependency element of each morpheme is “” or “is”, the sentence structure analysis unit 430 applies the subject (subject) to the morpheme before the dependency element. Or a leading character). For example, when the dependency element of each morpheme is “NO” or “NO”, the sentence structure analysis unit 430 determines that the morpheme before the dependency element is an object (target).
[0031]
Further, for example, when the dependency element of each morpheme is “Yes”, the sentence structure analysis unit 430 includes an action (predicate; this predicate is composed of a verb, an adjective, and the like). It is determined that
[0032]
The sentence structure analysis unit 430 that has determined the “case structure” of each morpheme that constitutes each clause determines the range of topics (topics) to be described later based on the first morpheme information associated with the determined “case structure”. A topic search command signal for specifying is output to the reflective determination unit 320.
[0033]
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, “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 a phrase composed of each morpheme.
[0034]
In this embodiment, as shown in FIG. 6, the “spoken sentence type” is a statement sentence (D; Declaration), an impression sentence (I; Impression), a conditional sentence (C; Condition), and a result sentence ( E; Effect, time sentence (T; Time), location sentence (L; Location), repulsion sentence (N; Negation), affirmative sentence (A; Answer), question sentence (Q; Question) It is.
[0035]
The statement sentence means a sentence composed of a user's opinion or idea, and in this embodiment, as shown in FIG. 6, for example, a sentence such as “I like Sato” can be cited. An impression sentence means the sentence which consists of an impression which a user holds. A place sentence means a sentence made up of place elements.
[0036]
A result sentence means a sentence composed of sentences including a result element for a topic. A time sentence means a sentence composed of sentences including temporal elements related to a topic.
[0037]
The conditional sentence means a sentence composed of sentences including elements such as a premise of a topic, a condition and a reason why the topic is established, when one utterance is regarded as a topic. The repulsive sentence means a sentence composed of a sentence including an element that repels a user's utterance partner. An example sentence for each “spoken sentence type” is as shown in FIG.
[0038]
That is, the utterance type determination unit 440 collates each phrase with each dictionary stored in the utterance type database 460 based on each phrase corresponding to the input sentence pattern signal, and from each phrase, Extract sentence elements related to the dictionary. The utterance type determination unit 440 that extracts sentence elements related to each dictionary from each phrase determines “spoken sentence type” based on the extracted sentence elements. The sentence element means the type of sentence for specifying the type of character string, and in this embodiment, the sentence element includes the above-described definition phrase (which means “-”).
[0039]
Here, as shown in FIG. 7, the utterance type database 460 includes a definition expression example dictionary having a dictionary related to a definition phrase (for example,), an affirmative phrase (for example, approval, sympathy, 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 dictionary with a dictionary related to, negative It consists of negative case dictionaries with dictionaries related to phrases (for example, not stupid, opposite), and each dictionary is associated with a “spoken sentence type”.
[0040]
As a result, the utterance type determination unit 440 compares the phrase with each dictionary stored in the utterance type database 460, extracts the sentence element related to each dictionary from the phrase, and associates it with the extracted sentence element. The “spoken sentence type” can be determined by referring to the determined type.
[0041]
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.
[0042]
The conversation database 500 stores a plurality of second morpheme information indicating a morpheme composed of one character, a plurality of character strings, or a combination thereof, and a plurality of reply contents to the user with respect to the utterance contents in association with each other in advance. Means (discourse storage means). The conversation database 500 is also an answer storage unit (discourse storage unit) that stores in advance a plurality of answer types indicating the types of answer contents associated with a plurality of answer contents in association with the second morpheme information.
[0043]
Furthermore, the conversation database 500 stores in advance a plurality of discourse ranges (keywords) indicating morphemes that constitute a range relevant to the input content that will be input by the user or the response content to the user. But there is. A plurality of second morpheme information indicating a morpheme made up of one character, a plurality of character strings, or a combination thereof is associated with the discourse range (keyword), and each second morpheme information includes a response content to the user. Associated with each.
[0044]
Furthermore, the conversation database 500 is also an answer storage means (discourse storage means) for classifying and storing each element constituting the second morpheme information into attributes such as each subject consisting of a main case and a target case consisting of a target case. .
[0045]
As shown in FIG. 8, in the present embodiment, the conversation database 500 is roughly divided in the present embodiment, which means a range that is related to the content of the speech that will be spoken by the user or the content of the response to the user. It consists of a range (discourse) and a topic (topic) that means a range that is most closely related to the content the user is speaking. As shown in the figure, “discourse range” is positioned as a superordinate concept of “topic” in the present embodiment.
[0046]
Each discourse range can be configured to have a hierarchical structure as shown in FIG. As shown in the figure, for example, a higher level discourse range (entertainment) for a certain discourse range (movie) is positioned in the upper hierarchical structure, and a lower level discourse range (movie) for the discourse range (movie). The attribute (movie) can be located in the lower hierarchical structure. That is, in the present embodiment, each discourse range can be arranged at a hierarchical position where the relationship between the higher concept, the lower concept, the synonym, and the synonym becomes clear with other discourse ranges.
[0047]
As described above, the discourse range is composed of each topic. In the present embodiment, for example, if the discourse range is an A movie name, it includes a plurality of topics related to “A movie name”. .
[0048]
This topic means a morpheme composed of a single character, a plurality of character strings, or a combination thereof, that is, each morpheme constituting speech content that will be uttered by the user. Each morpheme is associated with a subject (subject), an object (target case), and an action “case” (attribute). In this embodiment, each morpheme associated with these three elements is expressed as a topic title (this topic title corresponds to a subordinate concept of “topic”) (second morpheme information). .
[0049]
Note that the topic title is not limited to each morpheme associated with the above three elements, but other “cases”, that is, time meaning time (consisting of tense, mood, aspect, etc.), Each morpheme may be associated with a location meaning a place, a condition meaning a condition, an impression meaning an impression, an effect meaning a result, and the like.
[0050]
In this embodiment, the topic title (second morpheme information) is stored in advance in the conversation database 500, and the first morpheme information (derived from the utterance content uttered by the user) is It is a distinction.
[0051]
For example, if the talk range is “A movie name”, as shown in FIG. 10, the subject title is subject (A movie name), object (director), action (great) {this is “A movie name” The director of the name is composed of "meaning great".
[0052]
If there is no morpheme associated with “case composition” (subject, object, action, etc.) among the topic titles, “*” is indicated for the portion in the present embodiment.
[0053]
For example, {A movie name? } Is converted into a topic title (subject; object; action). }, “A movie name” can be specified as a subject, but “object” and “action” are not elements of the sentence, so the topic title is “subject” (A movie name) “No object” (*); no “action” (*) (see FIG. 10).
[0054]
The answer sentence means an answer sentence (answer contents) to be answered to the user, and is associated with each topic title (second morpheme information) in this embodiment (see FIG. 8). In this embodiment, as shown in FIG. 11, the answer sentence is a statement sentence (D; Declaration) or an impression sentence (I; Impression) in order to make an answer corresponding to the type of utterance sentence uttered by the user. , Conditional statement (C; Condition), result statement (E; Effect), time statement (T; Time), location statement (L; Location), negative statement (N; Negation), affirmative statement (A; Answer), question It is classified into types (answer types) such as sentences (Q).
[0055]
That is, as shown in FIG. 12, each answer sentence is associated with, for example, a discourse range (Sato) {subordinate concept; home run, superordinate concept; grass baseball, synonym; panda Sato, Sato player, panda} and each topic title. It has been.
[0056]
As shown in the figure, for example, the topic title 1-1 is {(Sato; *; I like): this consists of the order of (subject; object; action) as described above. If the order is the same below, the answer sentence 1-1 corresponding to the topic title 1-1 is (DA; statement affirmation “I like Sato”), (IA; comment affirmation) "I like Sato very much"), (CA; conditional affirmation sentence "Sato's home run is very impressive"), (EA; a result affirming sentence "I always watch Sato's games on TV"), (TA: Time affirmative sentence "I actually like it from the five-bats continual refrain in Koshien"), (LA; Place affirmative sentence "I like the serious face when standing on the blow"), (NA A repulsive affirmative sentence "I don't want to talk to people who don't like Sato, goodbye").
[0057]
In the present embodiment, as shown in FIG. 2, the conversation control unit 300 includes a management unit 310, a reflexive determination unit 320, a turnback determination unit 330, a discourse range determination unit 340, and an abbreviated sentence complement unit 350. , A topic search unit 360 and an answer sentence search unit 370.
[0058]
The management unit 310 controls the entire conversation control unit 300. Specifically, the management unit 310 to which the character string signal is input from the input unit 100 or the voice recognition unit 200 outputs the input character string signal to the morpheme extraction unit 410. In addition, the management unit 310 outputs the answer sentence searched by the answer sentence search unit 370 to the output unit 600.
[0059]
The reflexive determination unit 320 is a fixed form acquisition unit that collates the first morpheme information extracted by the morpheme extraction unit 410 with each fixed content, and searches the fixed content including the first morpheme information from each fixed content. .
[0060]
Here, the standard content means reflection element information for replying a standard content to the utterance content from the user, and this reflection element information is stored in the reflection element database 801 (standard storage means) in advance. A plurality are 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?""Typicalelements" such as
[0061]
Specifically, the reflexive determination unit 320 to which the topic search command signal is input from the sentence structure analysis unit 430 receives the first morpheme information included in the input topic search command signal and the reflection element database 801. The reflection element information is collated, the reflection element information including the first morpheme information is searched from the reflection element information, and the searched reflection element information is output to the management unit 310.
[0062]
That is, assuming that the reflection element information is D1 and the first morpheme information is W, the reflective determination unit 320 performs the reflective response when determining that the relationship of W∩D1 ≠ 0 is established. Perform the process.
[0063]
For example, when the user utters the utterance content “Good morning”, the reflexive determination unit 320 collates the utterance content “Good morning” with each reflection element information, and the utterance content from each reflection element information. The reflection element information “good morning” including (matching) “good morning” is searched, and the searched reflection element information “good morning” is output to the management unit 310.
[0064]
When the reflection determination unit 320 cannot search the reflection element information including the utterance content from the reflection element information, the reflex determination unit 320 returns the topic search command signal input from the sentence structure analysis unit 430. Output to.
[0065]
The return determination unit 330 collates the current first morpheme information extracted by the morpheme extraction unit 410 with the past response content stored in the return element database 802, and the current first morpheme information is a past response. If included in the content, it is a fixed form acquisition means for acquiring the content of the agreement.
[0066]
Here, “turnback” means to say back the content of the user's utterance as it is (or content close to it) in this embodiment. In this embodiment, the return element is composed of the first morpheme information that constitutes the response content output from the conversation control device 1 immediately before. For example, as shown in FIG. (Horse; beautiful; *), "I like Sato"(Sato;*; I like).
[0067]
Further, the return element database 802 is also an agreement storage means for preliminarily storing agreement contents for agreeing to input information input by the user. The content of the agreement includes, for example, the input information previously input by the user (if the previous input information by the user is “A film name director is Mr. S”, the content of the agreement is “ The director of the A movie name is Mr. S)), or “Yes”, “It is true”.
[0068]
Specifically, the return determination unit 330 to which the topic search command signal is input from the reflective determination unit 320 configures the first morpheme information and the return element included in the input topic search command signal for each return element. Each morpheme is collated, and it is determined whether or not the first morpheme information is included in the return element (see FIG. 14).
[0069]
If it is determined that the first morpheme information is included in each return element, the return determination unit 330 acquires the content of the agreement and outputs an answer sentence including the acquired content of the agreement to the management unit 310 (return) Process). That is, assuming that the return element (such as the previous answer sentence) is S and the first morpheme information is W, the return determination unit 330 performs the return process described above when the relationship of W⊂S ≠ 0 is established. I do.
[0070]
For example, the conversation control device 1 responds with “The director of the A movie name is Mr. S” (Director of the A movie name; Mr. S; *) (the order is the subject, the object, the order of the action, and so on. ) Is output, and then the user responds with a response if the utterance is “is the director of A movie name Mr. S” (director of A movie name; Mr. S; *)? Since the determination unit 330 matches the first morpheme information of the user (Director of A movie name; Mr. S; *) and each morpheme of the answer sentence (Director of A movie name; Mr. S; *), The user concludes that he / she is replying to the contents of the reply, obtains the stored agreement contents “Yes”, and outputs the obtained agreement contents.
[0071]
Further, the return determination unit 330 collates the current first morpheme information extracted by the morpheme extraction unit 410 with the past first morpheme information stored in the return element database 802 to obtain the current first morpheme information. Is included in the past first morpheme information, it is also a fixed form acquisition means for acquiring the repulsion content.
[0072]
Specifically, when the user utters the utterance content “Horse is beautiful” and the conversation control device 1 outputs the content “Horse is good” as the response content When the person repeats the utterance content that “the horse is beautiful”, the turn-back determination unit 330 determines that each morpheme (first morpheme information) {horse; beautiful; Each morpheme (first morpheme information) {horse; beautiful; *} that constitutes the content of the previous utterance “horse is beautiful” matches the response content from the conversation control device 1 so that the user You can conclude that you have not heard at all about "I feel good."
[0073]
In this case, since the user has not heard the response content from the conversation control device 1, the return determination unit 330 acquires the stored repulsion content (for example, do not repeat the same content), and the acquired repulsion The contents can be output.
[0074]
On the other hand, if the reversion determining unit 330 determines that the first morpheme information is the same as the content of the previous answer sentence or the first morpheme information is not the same as the previous first morpheme information, the reflex determination unit 320 The input topic search command signal is output to the conversation range determination unit 340.
[0075]
In addition, although the said return determination part 330 has shown the process in case a user makes a return with respect to "the reply content of the conversation control apparatus 1," the following processes can also be performed. For example, when the output unit 600 outputs an answer sentence “Horse is beautiful”, the user answers “Why is the horse beautiful?”, “Why is it beautiful?”, Or “Why?” This is a process of the turn-back determination unit 330 performed when the utterance is made.
[0076]
In this case, the return determination unit 330 outputs the response 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⊂S ≠ 0, c ≠ 0 (where c means the utterance type of W, and this utterance type is determined by the utterance type determination unit 440 described later). As will be described later, for example, there is a question sentence, etc., as will be described later. Therefore, a “conditional” reply process (the user performed a reply with a question sentence on the answer contents) Process).
[0077]
For example, when the conversation control device 1 outputs an answer sentence “The horse is beautiful”, the above-mentioned user utters the content of the utterance “Why is the horse beautiful?”. At that time, in order to resolve the user's question, the return determination unit 330 acquires an answer sentence such as “Even the horse is not beautiful” from the return element database 802, and the acquired answer sentence is sent to the management unit 310. Process to output.
[0078]
The discourse range determination unit 340 collates the first morpheme extracted by the phrase analysis unit 420 with each discourse range, and searches the discourse range for a discourse range that matches the morpheme included in the first morpheme information. It is a discourse search means.
[0079]
Specifically, the conversation range determination unit 340 to which the topic search command signal is input from the turn-back determination unit 330 determines the user's conversation range based on the input talk search command signal. That is, based on the input search command signal, the conversation range determination unit 340 searches the conversation database 500 for a range (discourse range) relevant to the content spoken by the user.
[0080]
For example, the conversation range determination unit 340 determines that the first morpheme information included in the input topic search command signal is (interesting movie; *; *) {is there an interesting movie? }, It is determined whether the “movie” included in the first morpheme information is included in the discourse range group stored in the conversation database 500.
[0081]
When the “movie” included in the first morpheme information is included in the conversation range group stored in the conversation database 500, the conversation range determination unit 340 determines the “movie” as the conversation range and determines it. The discourse range is included in the topic search command signal and output to the abbreviated sentence complementing unit 350.
[0082]
When the conversation range determination unit 340 determines that the conversation range of “movie” included in the first morpheme information is not included in the conversation range group stored in the conversation database 500, the conversation range determination unit 340 relates to the first morpheme information. Answer sentence to be obtained is acquired from the conversation database 500, and the acquired answer sentence is output to the management unit 310.
[0083]
Thereby, the topic search unit 360 described later collates each “topic title” belonging to the “discourse range” determined by the conversation range determination unit 340 with the first morpheme information specified by the sentence structure analysis unit 430. Therefore, it is unnecessary to collate “all” “topic titles” (second morpheme information) with the first morpheme information, and the answer sentence search unit 370 to be described later will search for the final answer sentence. Can be shortened.
[0084]
The abbreviated sentence complementing unit 350 searches the attributes (subjects, objects, actions, etc.) constituting the first morpheme information based on the first morpheme information extracted by the phrase analysis unit 420 for attributes that do not include a morpheme. Attribute search means. The abbreviated sentence complementing unit 350 is also a morpheme adding unit that adds a morpheme constituting the discourse range searched by the discourse range determining unit 340 to the attribute based on the searched attribute.
[0085]
Specifically, the abbreviated sentence complementing unit 350 to which the topic search command signal is input from the discourse range determination unit 340 is based on the first morpheme information included in the input discourse search command signal, and the utterance including the first morpheme information. It is determined whether or not the content is an abbreviated sentence. If the utterance content including the first morpheme information is an abbreviated sentence, the morpheme in the discourse range to which the first morpheme information belongs is added to the first morpheme information.
[0086]
For example, the abbreviation sentence complementing unit 350 has a morpheme constituting the first morpheme information included in the input topic search command signal (director; *; *) (director?) (This sentence is “what” director If it is unknown, it means an abbreviated sentence.), The discourse range determined by the discourse range determination unit 340 (A movie name; this A movie name indicates the title of the movie) If it is the first morpheme information belonging to A), the determined discourse range (A movie name) is added to the first morpheme information to the morpheme constituting the first morpheme information (director of “A movie name”; *; *) Yes.
[0087]
That is, assuming that the first morpheme information is W, the determined discourse range is D, and the current discourse range is d, the abbreviated sentence complementing unit 350 determines that if the relationship of W 情報 (dεD) holds, The morpheme information W is converted into W∪ (dεD) = W ′, and the converted first morpheme information is included in the topic search command signal and output to the topic search unit 360. If the abbreviated sentence complementing unit 350 determines that the utterance content corresponding to the first morpheme information included in the input topic command signal is not an abbreviated sentence, it outputs the input topic search command signal to the topic search unit 360. To do.
[0088]
Thereby, even if the first morpheme information is an abbreviated sentence and it is not clear as Japanese, the abbreviated sentence complementing unit 350, when 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; *; *) {What is the director of A movie name? }, Even if the user's utterance content is an abbreviated sentence, the abbreviated sentence can be supplemented based on the determined discourse range, and the abbreviated sentence can be clarified. it can.
[0089]
For this reason, the first morpheme information is set so that the abbreviated sentence complementing unit 350 has the proper utterance contents constituting the first morpheme information even if the utterance contents constituting the first morpheme information are abbreviated sentences. Since the specific morpheme can be complemented, the topic search unit 360 acquires the optimal “topic title” (second morpheme information) related to the first morpheme information based on the first morpheme information after the complement. The answer sentence search unit 370 can output the answer content more suitable for the user's utterance content based on the “topic title” acquired by the topic search unit 360.
[0090]
The topic search unit 360 collates the first morpheme information extracted by the phrase analysis unit 420 or the first morpheme information supplemented by the abbreviated sentence complement unit 350 with each second morpheme information, It is the 1st search means which searches the 2nd morpheme information containing the morpheme which comprises 1st morpheme information from inside.
[0091]
Specifically, the topic search unit 360 to which the topic search command signal is input from the abbreviated sentence complement unit 350 is determined by the discourse range determination unit 340 based on the first morpheme information included in the input topic search command signal. The “topic title” including the morpheme of the first morpheme information is searched from each “topic title” (second morpheme information) belonging to the discourse range, and the search result signal is used as a search result signal to search the answer sentence search unit 370 and Output to the utterance type determination unit 440.
[0092]
For example, when the “case configuration” constituting the first morpheme information is (Sato; *; I like) {I like Sato}, the topic search unit 360, as shown in FIG. Each morpheme (Sato; *; I like) belonging to the “composition” is compared with each topic title 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; *; likes) that matches (or approximates) each morpheme (Sato; *; likes) belonging to the “case composition” is searched, and this search result is used as a search result signal as a response sentence. The data is output to the search unit 370 and the utterance type determination unit 440.
[0093]
The utterance type determination unit 440 to which the search result signal is input from the topic search unit 360, based on the input search result signal, an answer search command for searching for a specific answer sentence that answers to the corresponding user. A signal (this answer search command signal also includes the determined “sentence type”) is output to the answer sentence search unit 370.
[0094]
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. In addition, 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 means for searching for an answer type that matches the user's utterance type from among the answer types.
[0095]
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 are input, the topic title (search result) corresponding to the input search result signal. Based on the second morpheme information) and the “speech sentence type” (utterance type) corresponding to the answer search command signal, the answer sentence group (each answer content) associated with the “topic title”. Among them, an answer sentence having an answer type (this answer type means “type of answer sentence” shown in FIG. 11) that matches the “sentence sentence type” (DA, IA, CA, etc.) is searched.
[0096]
For example, when the topic title corresponding to the search result is the topic title 1-1 (Sato; *; I like) shown in FIG. 12, the answer sentence search unit 370 is associated with the topic title 1-1. Of the reply sentences 1-1 (DA, IA, CA, etc.), the reply composed of the reply type (DA) that matches the “spoken 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.
[0097]
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 determination unit 320 or the contents of the turn-back process from the turn-back determination unit 330, the answer sentence corresponding to the input reflection element information, the content of the turn-back process that is input To the output unit 600.
[0098]
The output unit 600 is an output unit that outputs the answer text acquired by the answer text search unit 370. In this embodiment, for example, a speaker, a display, and the like can be given. Specifically, the output unit 600 to which an answer sentence is input from the management unit 310 outputs the input answer sentence {for example, I also like Sato}.
[0099]
(Conversation control method using conversation control device)
The conversation control method by the conversation control apparatus 1 having the above configuration can be implemented by the following procedure. FIG. 15 is a flowchart showing the procedure of the conversation control method according to the present embodiment.
[0100]
First, the input unit 100 performs a step of acquiring the utterance content from the user (S101). Specifically, the input unit 100 acquires the voice that constitutes the utterance content of the user, and outputs the acquired voice to the voice recognition unit 200 as a voice signal. Further, the input unit 100 identifies a character string corresponding to the input information (other than the voice) based on the input information (other than the voice) input from the user, and the conversation control unit uses the identified character string as a character string signal. Output to 300.
[0101]
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 a speech signal is input from the input unit 100 analyzes the input speech signal, and a character string corresponding to the analyzed speech signal is stored 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.
[0102]
And the morpheme extraction part 410 performs the step which extracts each morpheme which comprises the minimum unit of a character string as 1st morpheme information based on the character string specified by the speech recognition part 200 (S103).
[0103]
Specifically, the morpheme extraction unit 410 to which the character string signal is input from the management unit 310 includes a character string corresponding to the input character string signal and nouns, adjectives, verbs, and the like stored in advance in the morpheme database 450. The morpheme group is collated, each morpheme (m1, m2,...) Matching the morpheme group is extracted from the character string, and each extracted morpheme is output to the phrase analysis unit 420 as an extraction signal.
[0104]
Then, the phrase analysis unit 420 performs a step of grouping 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 morphemes corresponding to the input extraction signal to combine them into a phrase format.
[0105]
That is, as shown in FIG. 4, the phrase analysis unit 420 extracts and extracts the dependency elements (for example, gahahahahaha ...) of each morpheme based on each morpheme corresponding to the input extraction signal. Each morpheme is grouped into each clause based on the dependency element.
[0106]
The phrase analysis unit 420 that collects each morpheme into each phrase includes a sentence structure analysis unit 430 and an utterance type determination unit 440 using sentence pattern information including each phrase that combines each morpheme and each morpheme constituting each phrase as a sentence pattern signal. Output to.
[0107]
Thereafter, 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 case and target case (S105). Specifically, the sentence structure analysis unit 430, to which the sentence pattern signal is input from the phrase analysis unit 420, determines each morpheme included in the phrase based on each morpheme corresponding to the input sentence pattern signal and the phrase composed of each morpheme. Determine the “case composition”.
[0108]
That is, as shown in FIG. 5, for example, when the dependency element of each morpheme is “” or “is”, the sentence structure analysis unit 430 applies the subject (subject) to the morpheme before the dependency element. Or a leading character). For example, when the dependency element of each morpheme is “NO” or “NO”, the sentence structure analysis unit 430 determines that the morpheme before the dependency element is an object (target).
[0109]
Further, for example, when the dependency element of each morpheme is “Yes”, the sentence structure analysis unit 430 includes an action (predicate; this predicate is composed of a verb, an adjective, and the like). It is determined that
[0110]
The sentence structure analysis unit 430 that has determined the “case structure” of each morpheme that constitutes each clause determines the range of topics (topics) to be described later based on the first morpheme information associated with the determined “case structure”. A topic search command signal for specifying is output to the topic search unit 360.
[0111]
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, “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 a phrase composed of each morpheme.
[0112]
That is, the utterance type determination unit 440 collates each phrase with each dictionary stored in the utterance type database 460 based on each phrase corresponding to the input sentence pattern signal, and from each phrase, Extract sentence elements related to the dictionary. The utterance type determination unit 440 that extracts sentence elements related to each dictionary from each phrase determines “spoken sentence type” based on the extracted sentence elements.
[0113]
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.
[0114]
Next, the reflexive determination unit 320 compares the first morpheme information extracted by the morpheme extraction unit 410 with each fixed content, and performs a step of searching for fixed content including the first morpheme information from each fixed content. (S107: reflective processing).
[0115]
Specifically, the reflexive determination unit 320 to which the topic search command signal is input from the sentence structure analysis unit 430 receives the first morpheme information included in the input topic search command signal and the reflection element database 801. The reflection element information (standard content) is collated, 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.
[0116]
When the reflection element information cannot be searched for the reflection element information including the first morpheme information from the reflection element information, the reflection determination unit 320 determines whether to return the topic search command signal input from the sentence structure analysis unit 430. To the unit 330.
[0117]
Next, the return determination unit 330 collates the first morpheme information extracted by the morpheme extraction unit 410 with each return element, and performs a step of searching for the return element including the first morpheme information from each return element ( S108;
[0118]
When it is determined that the first morpheme information is included in each return element, the return determination unit 330 acquires the return element including the first morpheme information, and manages the response sentence including the acquired return element. The data is output to the unit 310 (turnback processing). That is, assuming that the return element (answer sentence output last time, utterance content spoken by the previous user, etc.) is S and the first morpheme information is W, the return determination unit 330 establishes a relationship of W⊂S ≠ 0. If so, the above-described turning process is performed.
[0119]
On the other hand, when determining that the first morpheme information is not included in each return element, the return determination unit 330 sends the topic search command signal input from the reflective determination unit 320 to the conversation range determination unit 340. Output.
[0120]
Then, the discourse range determination unit 340 compares the first morpheme extracted by the phrase analysis unit 420 with each discourse range, and performs a step of searching the discourse range including the first morpheme information from each discourse range. (S109).
[0121]
Specifically, the conversation range determination unit 340 to which the topic search command signal is input from the reversal determination unit 330 is based on the input search command signal, and the content that the user is speaking from the conversation database 500. Search for a relevant range (discourse range).
[0122]
For example, the conversation range determination unit 340 determines that the first morpheme information included in the input topic search command signal is (interesting movie; *; *) {is there an interesting movie? }, It is determined whether the “movie” included in the first morpheme information is included in the discourse range group stored in the conversation database 500.
[0123]
When the “movie” included in the first morpheme information is included in the conversation range group stored in the conversation database 500, the conversation range determination unit 340 determines the “movie” as the conversation range and determines it. The discourse range is included in the topic search command signal and output to the abbreviated sentence complementing unit 350.
[0124]
When the conversation range determination unit 340 determines that the conversation range of “movie” included in the first morpheme information is not included in the conversation range group stored in the conversation database 500, the conversation range determination unit 340 relates to the first morpheme information. Answer sentence to be obtained is acquired from the conversation database 500, and the acquired answer sentence is output to the management unit 310.
[0125]
Next, the abbreviation sentence complementing unit 350 includes attributes that do not include a morpheme 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. Perform the step of searching. Thereafter, the abbreviated sentence complementing unit 350 performs a step of adding the morpheme constituting the discourse range searched by the discourse range determining unit 340 to the attribute based on the attribute not including the searched morpheme (S110; abbreviated sentence). Complement).
[0126]
Specifically, the abbreviated sentence complementing unit 350 to which the topic search command signal is input from the discourse range determination unit 340 is based on the first morpheme information included in the input discourse search command signal, and the utterance including the first morpheme information. It is determined whether or not the content is an abbreviated sentence. If the utterance content including the first morpheme information is an abbreviated sentence, the morpheme in 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 has a morpheme constituting the first morpheme information included in the input topic search command signal (director; *; *) (director?) (This sentence is “what” director If it is unknown, it means an abbreviated sentence.), The discourse range 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 a certain morpheme, the morpheme (A movie name) of the determined discourse range is added to the first morpheme information to the morpheme constituting the first morpheme information (director of “A movie name”); *; *)
[0128]
That is, assuming that the first morpheme information is W, the determined discourse range is D, and the current discourse range is d, the abbreviated sentence complementing unit 350 determines that if the relationship of W 情報 (dεD) holds, The morpheme information W is converted into W∪ (dεD) = W ′, and the converted first morpheme information is included in the topic search command signal and output to the topic search unit 360. If the abbreviated sentence complementing unit 350 determines that the utterance content corresponding to the first morpheme information included in the input topic command signal is not an abbreviated sentence, it outputs the input topic search command signal to the topic search unit 360. To do.
[0129]
Next, the topic search unit 360 collates the first morpheme information extracted by the phrase analysis unit 420 or the first morpheme information supplemented by the abbreviated sentence complement unit 350 with each second morpheme information, and each second morpheme A step of searching for second morpheme information including morpheme constituting the first morpheme information from the information is performed (S111).
[0130]
Specifically, the topic search unit 360 to which the topic search command signal is input from the abbreviated sentence complement unit 350 is determined by the discourse range determination unit 340 based on the first morpheme information included in the input topic search command signal. The “topic title” including the morpheme of the first morpheme information is searched from each “topic title” (second morpheme information) belonging to the discourse range, and the search result signal is used as a search result signal to search the answer sentence search unit 370 and Output to the utterance type determination unit 440.
[0131]
For example, when the “case configuration” constituting the first morpheme information is (Sato; *; I like) {I like Sato}, the topic search unit 360, as shown in FIG. Each morpheme (Sato; *; I like) belonging to the “composition” is compared with each topic title 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; *; likes) that matches (or approximates) each morpheme (Sato; *; likes) belonging to the “case composition” is searched, and this search result is used as a search result signal as a response sentence. 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, based on the input search result signal, an answer search command for searching for a specific answer sentence that answers to the corresponding user. A signal (this answer search command signal also includes the determined “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 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, A search is made for a response type that matches the utterance type of the user from among the response types, and a step of obtaining an answer sentence associated with the searched response 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 are input, the topic title (search result) corresponding to the input search result signal. Based on the second morpheme information) and the “speech sentence type” (utterance type) corresponding to the answer search command signal, the answer sentence group (each answer content) associated with the “topic title”. Among them, an answer sentence having an answer type (this answer type means “type of answer sentence” shown in FIG. 11) that matches the “sentence sentence type” (DA, IA, CA, etc.) is searched.
[0135]
For example, when the topic title corresponding to the search result is the topic title 1-1 (Sato; *; I like) shown in FIG. 12, the answer sentence search unit 370 is associated with the topic title 1-1. Of the reply sentences 1-1 (DA, IA, CA, etc.), the reply composed of the reply type (DA) that matches the “spoken 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 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 determination unit 320 or the contents of the turn-back process from the turn-back determination unit 330, the answer sentence corresponding to the input reflection element information, the content of the turn-back process that is input To the output unit 600. The output unit 600 to which an 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 conversation control system and conversation control method)
According to the invention according to 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 fixed content stored in advance, and each fixed content 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]
In addition, when the user's utterance content is a fixed content, the reflexive determination unit 320 replies with the fixed content (greeting etc.), so that the user first contacts the conversation control device 1. You can enjoy a sense of communication.
[0139]
Further, the reversal determination unit 330 compares the current first morpheme information with the past response content, and if the current first morpheme information is not included in the past response content, the agreement stored in advance is stored. Since the contents can be acquired, if the input information currently input from the user matches the past response contents, the return determination unit 330 returns the user to the previous response contents (use It is possible to conclude that the user has input the input information that the person is listening to the response content.
[0140]
In this case, the return determination unit 330 acquires the contents of the agreement that has been stored and the acquired agreement (for example, “That ’s right”) because the user has made a response to the previous response. Can be output. As a result, if the user does not understand the meaning of the answer content output from the conversation control device 1, he / she can listen again and use the answer content again, so that the user is also having a conversation with another user. You can taste a feeling like this.
[0141]
Further, the reversal determination unit 330 collates 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, the repulsion content is acquired. Therefore, when the input information input last time is included in the input information input this time, the user may repeatedly input the same content as the previous input information. Therefore, it can be determined that the user has not properly answered the response content from the conversation control device.
[0142]
In this case, since the user does not appropriately reply to the previous response content, the reversal determination unit 330 repels the user, so the stored repulsion content is acquired, and the acquired repulsion content Is output. As a result, if the user does not input appropriate input information with respect to the response content from the conversation control device 1, the repulsion content is output from the conversation control device 1. You can taste a sense of being.
[0143]
Further, in order to search for the second morpheme information approximate to the first morpheme information, the topic search unit 360 may collate each second morpheme information belonging to the “discourse range” with the first morpheme information. Since it is not necessary to collate the second morpheme information with the first morpheme information, the time until the second morpheme information approximate to the first morpheme information can be shortened.
[0144]
As a result, the topic search unit 360 can search (pinpoint search) the second morpheme information that approximates the first morpheme information in a short time, so that the answer sentence search unit 370 is the topic search unit 360. An answer sentence associated with the second morpheme information can be acquired in a short time based on the searched second morpheme information, and the conversation control device 1 quickly answers the utterance content from the user. be able to.
[0145]
Moreover, the topic search part 360 searches the 2nd morpheme information which contains the morpheme (element which comprises a user's utterance content) which comprises 1st morpheme information from each 2nd morpheme information, and an answer sentence search part Since 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 can obtain the utterance content of the user. Based on each constituent morpheme (first morpheme information), it is possible to take into account the semantic spaces (subjects, objects, etc.) constructed by each morpheme and obtain the response contents created in advance based on such semantic spaces Thus, it is possible to acquire the answer content more suitable for the utterance content, rather than simply using the entire utterance content as a keyword and obtaining the answer content associated with the keyword.
[0146]
Further, since the topic search unit 360 searches for the second morpheme information including the first morpheme information, it is not necessary to search for the second morpheme information that completely matches the utterance content of the user, and the conversation control device 1 is developed. The developer who does not need to memorize a huge amount of answer contents corresponding to the utterance contents that will be uttered by the user in advance, and can reduce the capacity of the storage unit.
[0147]
Furthermore, the answer sentence search unit 370 selects the answer type that matches the user's utterance type from the answer types (description, affirmation, location, repulsion, etc.) associated with each second morpheme information belonging to the “discourse range”. Since the response content associated with the response type can be acquired based on the searched response type, the conversation control device 1 can determine the utterance type that constitutes the user's conversation content, for example, the user Answers that match the user's utterance type out of multiple answers based on what is simply stated, what the user has to say, what the user describes the location element, etc. As a result, it is possible to obtain an optimal answer to the corresponding user.
[0148]
Furthermore, the answer sentence search unit 370 matches the user's utterance type from the answer types associated with the second morpheme information belonging only to the “discourse range” searched by the discourse range determination unit 340. Since it is only necessary to search for the type (pinpoint search is possible), it is not necessary to search for the response type associated with the “all” second morpheme information and the user's utterance type one by one. Can be obtained in a short time.
[0149]
Finally, the abbreviated sentence complementing unit 350 belongs to the discourse range in which the first morpheme information exists even if the first morpheme information constituting the utterance content of the user is an abbreviated sentence and is not clear as Japanese. If so, the discourse range can be added to the first morpheme information, and the first morpheme information consisting of abbreviated sentences can be complemented.
[0150]
Thus, the abbreviated sentence complementing unit 350 allows the first morpheme information so that the utterance contents constituting the first morpheme information are appropriate Japanese even if the utterance contents constituting the first morpheme information are abbreviated sentences. Since a specific morpheme (such as a morpheme constituting a discourse range) can be complemented, the topic search unit 360 is based on the first morpheme information after completion supplemented by the abbreviated sentence complement unit 350. The optimal second morpheme information related to the information can be acquired, and the answer sentence search unit 370 can select the answer content more suitable for the user's utterance content based on the second morpheme information acquired 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 does not use a function such as a neuro network or an AI intelligence, and does not mean what the abbreviated sentence means through past search results. Since the developer of the conversation control device 1 does not need to install a neuro network or AI intelligence, the system of the conversation control device 1 can be constructed more simply.
[0152]
[Example of change]
In addition, this invention is not limited to the said embodiment, The change as shown below can be added.
[0153]
(First change example)
In this modification, the conversation database 500 may be an element storage unit that stores a plurality of pieces 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 collates 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 the character string uttered by the user are similar. For example, as shown in FIG. 16, if the element information indicating the entire group is “gift”, the “gift” is similar to a present, gift, year-end gift, mid-year gift, celebration, etc. (group). Therefore, when there is a morpheme similar to “gift” (such as the present), the morpheme extraction unit 410 can handle the similar morpheme as “gift”.
[0155]
That is, for example, when the morpheme extracted from the character string is “present”, the morpheme extraction unit 410 has “present” as the element information representing “present” as shown in FIG. “Present” can be replaced with “Gift”.
[0156]
This allows the morpheme extraction unit 410 to sort out morphemes that are similar to each other, so that the developer who develops the conversation control device can perform the first corresponding to the semantic space that is grasped from the mutually similar first morpheme information. It is not necessary to create reply contents related to the bimorphic 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 modified example)
As shown in FIG. 17, in the present modification example, the topic search unit 360 may include a ratio calculation unit 361 and a selection unit 362.
[0158]
The ratio calculation unit 361 compares the first morpheme information extracted by the morpheme extraction unit 410 with each second information, and the ratio of the first morpheme information to the second morpheme information for each second morpheme information. Is a calculation means for calculating.
[0159]
Specifically, the ratio calculation unit 361 to which the topic search command signal is input from the sentence structure analysis unit 430, based on the first morpheme information included in the input topic search command signal, as shown in FIG. One morpheme information is collated with each topic title (second morpheme information) belonging to the discourse range stored in the conversation database 500, and the first morpheme information occupies in each topic title for each topic title. Calculate the percentage.
[0160]
For example, as shown in FIG. 17, when 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 belonging to “case composition” is matched with each morpheme belonging to “case composition” by comparing each morpheme belonging to “case composition” (Sato; *; likes) and each morpheme included in the topic title (Sato; *; likes). The ratio of (Sato; *; I like) is calculated to be 100%. The ratio calculation unit 361 performs these calculations for each topic title, and outputs each calculated ratio to the selection unit 362 as a ratio signal.
[0161]
The selection unit 362 is a selection unit that selects one second morpheme information from each second morpheme information according to the size of each rate calculated by the rate calculation unit 361 for each second morpheme information. 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 included in the input ratio signal (element of “case configuration” / element of “topic title” × 100). For example, a topic title with a high ratio is selected (see FIG. 18). The selection unit 362 that has selected a topic title with a high ratio outputs the selected topic title to the answer sentence search unit 370 and the utterance type determination 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 selection unit 362 calculates the ratio of the first morpheme information to the second morpheme information for each second morpheme information, and sets the size of each ratio calculated for each second morpheme information. Accordingly, since one second morpheme information can be selected from each second morpheme information, the selection unit 362 has, for example, the first morpheme information (what constitutes the utterance content of the user) first. If the second morpheme information that accounts for a large proportion of the dimorphic information can be acquired from a plurality of second morpheme information groups, the second morpheme information that follows the semantic space grasped from the first morpheme information can be obtained more accurately. As a result, the answer sentence search unit 370 can make an optimum answer to the utterance content of the user.
[0164]
Further, since the selection unit 362 can select a topic title having a high ratio calculated by the ratio calculation unit 361 from a plurality of topic titles, the selection unit 362 belongs to the “case configuration” included in the user's utterance sentence. 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, since the selection unit 362 can acquire a topic title closely related to the “case configuration” constituting the first morpheme information, the developer who develops the conversation control device 1 configures the first morpheme information. Since it is not necessary to store topic titles that completely match “case configuration” in the conversation database 500, 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 “discourse range” searched by the discourse range determination unit 340. , It is not necessary to calculate the ratio of the first morpheme information to the “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, it is possible to quickly output the optimum answer contents for the utterance contents from the user based on the acquired second morpheme information.
[0167]
The ratio calculation unit 361 collates each morpheme of the first morpheme information belonging to each classified attribute and each morpheme of each second morpheme information belonging to each attribute stored in advance for each attribute. It may be a first search means for searching for second morpheme information including 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 is input, for each “case” (subject; object; action) of the “case configuration” included in the input topic search command signal. ”And each morpheme belonging to“ case ”of the topic title composed of the same“ case ”are collated, and it is determined whether or not the morphemes constituting each“ case ”are the same.
[0169]
For example, as illustrated in FIG. 19, when the “case” morpheme of “case configuration” is (dog; person; bitten) {dog bites a person}, the ratio calculation unit 361 displays those morphemes. Match "dog", "person", and "chewed" with the morpheme "dog", "person", and "chewed" of the topic title consisting of the same "case" that constitutes the morpheme Then, among the morphemes “dog”, “people”, and “chewing” that make up the topic title, the “case composition” morpheme “dog” consisting of the same “case” corresponding to each morpheme, The ratio of “people” and “biting” is calculated (100%).
[0170]
If the element constituting the topic title is (person; dog; bite) {person bites the dog}, the ratio calculation unit 361 performs morphemes belonging to two cases by the same procedure as described above. Therefore, the degree of coincidence of each “case” between the morpheme constituting “case composition” and “topic title” is calculated to be 33% (see FIG. 19).
[0171]
The ratio calculation unit 361 that has calculated the ratio selects a topic title with a high ratio from 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]
As a result, the ratio calculation unit 361 displays, for each “case”, each morpheme of the first morpheme information belonging to each classified “case configuration” (subject case, target case, etc.) and a pre-stored topic title. Since 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 calculator 361 is different from the normal word order. If the utterance content is composed of things, for example, “a person bites a dog”, the morpheme of the subject case is “person” and the morpheme of the subject case is “dog”. You can search for matching second morpheme information, and obtain the response contents {"really?" Or "I don't know the meaning"} associated with the second morpheme information (person; dog; bite) can do.
[0173]
That is, since the ratio calculation unit 361 can identify utterance contents that are difficult to identify, for example, “a person bites a dog” and “a dog bites a person”, an optimal answer to the identified utterance contents, For the former, for example, “Really?”, For the latter, for example, “Are you okay?”
[0174]
Further, the ratio calculation unit 361 may search for the second morpheme information including the morpheme of the first morpheme information in at least one attribute from the respective second morpheme information belonging to the “discourse range”. From the second morpheme information, it is no longer necessary to acquire one second morpheme information, the second morpheme information that follows the semantic space composed of the first morpheme information can be acquired in a shorter time, As a result, the conversation control device 1 can quickly output the optimum answer content for the utterance content from the user based on the acquired second morpheme information.
[0175]
(Third change example)
As shown in FIG. 20, the present modification is not limited to the above embodiment and each of the modifications described above, and the communication unit 800 in the conversation control devices 1 a and 1 b and the communication unit via the communication network 1000. A communication unit 900 for transmitting / receiving data to / from 800, conversation databases 500b to 500d connected to the communication unit 900, and servers 2a to 2c may be provided (conversation control system).
[0176]
Here, the communication network 1000 means a communication network that transmits and receives data. In the present embodiment, for example, the Internet is used.
[0177]
In this modified example, the conversation control devices 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. Also good. The servers 2a to 2c store contents similar to those stored in the conversation databases 500a to 500d.
[0178]
Thereby, the conversation control unit 300 not only includes the conversation database 500a arranged inside the conversation control device 1a but also the other conversation control device 1b, the conversation databases 500b to 500d, and the server 2a to the communication database 1000. 2c can be referred to, for example, it is possible to search the conversation database 500a for the discourse range related to each morpheme (first morpheme information) belonging to “case structure” 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, It is possible to search for an answer sentence more suitable for the utterance sentence.
[0179]
(Fourth change example)
The sentence structure analysis unit 430 may store in the conversation database 500 each “case configuration” and each “case configuration” constituting the identified first morpheme information. The answer sentence search unit 370 may store each “case structure” and each “morpheme” associated with each “case structure” constituting the searched answer sentence in the conversation database 500.
[0180]
The conversation range determination unit 340 may store the searched conversation range in the conversation database 500. The topic search unit 360 may store the searched second morpheme information in the conversation database 500.
[0181]
The first morpheme information, the second morpheme information, each “case composition” that constitutes the first morpheme information or the second morpheme information, each morpheme associated with each “case composition”, and the retrieved answer sentence Each “case structure” to be configured, each morpheme associated with each “case structure”, and the searched discourse range can be stored in the conversation database 500 as history morpheme information in association with each other.
[0182]
The abbreviated sentence complementing unit 350 does not include a morpheme from each attribute (subject, object, action, etc .; case configuration) constituting the first morpheme information based on the first morpheme information extracted by the phrase analysis unit 420. An attribute may be searched, and history morpheme information stored in the conversation database 500 may be added to the attribute based on the searched attribute.
[0183]
Specifically, the abbreviated sentence complementing unit 350 to which the topic search command signal is input from the discourse range determination unit 340 is based on the first morpheme information included in the input discourse search command signal, and the utterance including the first morpheme information. It is determined whether the content is an abbreviated sentence. If the utterance content including 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 stores The stored history form information is added to the first morpheme information.
[0184]
That is, assuming that 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 supplemented first morpheme information W1 is S1ＳW , O1∪W, A1∪W, or D1∪W.
[0185]
The topic search unit 360 collates the first morpheme information W1 supplemented by the abbreviated sentence complement unit 350 and each second morpheme information, and from each “topic title” (second morpheme information), the first morpheme information The second morpheme information including W1 is searched, and the searched topic title is output to the answer sentence search unit 370 and the utterance type determination unit 440 as a search result signal.
[0186]
Thereby, even if the utterance content composed of the first morpheme information is an abbreviated sentence and is not clear as Japanese, the abbreviated sentence complementing unit 350 uses the history form information stored in the conversation database 500, Since the omitted morpheme of the first morpheme information can be complemented, the utterance content including the omitted first morpheme information can be clarified.
[0187]
For this reason, when the abbreviated sentence complementing part 350 is the abbreviated sentence which comprises 1st morpheme information, 1st morpheme information is set so that the utterance content which consists of 1st morpheme information becomes appropriate Japanese. Since the morpheme omitted in FIG. 6 can be supplemented, the topic search unit 360 is based on the first morpheme information supplemented with the morpheme, and the optimal “topic title” (second morpheme) related to the first morpheme information. Information) can be acquired, and the answer sentence search unit 370 can output the answer content more suitable for the user's utterance content based on the optimal “topic title” acquired by the topic search unit 360. .
[0188]
(Fifth change example)
The topic search unit 360 may include a deletion unit 363 and a discourse addition unit 364, as shown in FIG. The deletion unit 363 collates the second morpheme information with the discourse range searched by the discourse range determination unit 340 based on the searched second morpheme information, and determines the discourse from each morpheme constituting the second morpheme information. It is a deletion means for deleting a morpheme that matches the range.
[0189]
Specifically, the topic search unit 360 to which the topic search command signal is input from the abbreviated sentence complement 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 matching the first morpheme information is searched from each second morpheme information.
[0190]
Then, based on the searched second morpheme information, the deletion unit 363 collates the second morpheme information with the morphemes constituting the discourse range determined by the discourse range determination unit 340, and stores the second morpheme information. Then, 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 364 as a delete signal.
[0191]
That is, the deletion unit 363 removes (removes) the current discourse range D2 (this D2 is made of morpheme) determined by the discourse range determination unit 340 from each morpheme t1 constituting the second morpheme information. If the result is t2, t2 = t1-D2).
[0192]
The discourse adding unit 364 acquires another discourse range associated with the discourse range searched by the discourse range determining unit 340 based on the second morpheme information from which the morpheme has been deleted by the deletion unit 363, and the acquired other This is a discourse adding means for adding a morpheme constituting a discourse range to second morpheme information.
[0193]
Specifically, when the current discourse range D2 is related to the answer sentence K1, and the discourse range is DK, other discourses related to the answer sentence K1 or the current discourse range D2 (those that have a sibling relationship). Since the range D3 can be expressed as D3 = D2∪DK, the second morpheme information W2 after adding the morpheme constituting the other discourse range D3 can be set to W2 = t2∪D3.
[0194]
For example, each morpheme t1 constituting the second morpheme information is (A movie name; *; interesting) {A movie name is interesting? }, And the current discourse range D2 determined by the discourse range determination unit 340 is (A movie name), the deletion unit 363 first starts from each morpheme t1 (A movie name; *; interesting). The conversation range D2 (A movie name) is deleted, and the deleted result is set to t2 (*; *; interesting) (t2 = t1-D2).
[0195]
When the other conversation range D3 related to the current conversation range D2 (A movie name) is “B movie name”, the second morpheme information after adding the morpheme constituting the other conversation range D3 W2 is t2∪D3, so (B movie name; *; funny) {B movie name is interesting? }.
[0196]
Thereby, when the user's utterance content is “A movie name is interesting?”, The discourse adding unit 364 matches each morpheme (A movie name; *; interesting) constituting the user's utterance content. Second morpheme information (A movie name; *; interesting), other second morpheme information (B movie name; *; interesting) {B movie name is interesting? }, 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 part 364, The acquired answer text can be output.
[0197]
As a result, the answer sentence search unit 370 does not output an answer sentence for the user's utterance content, but is related to the utterance content based on the second morpheme information including the morpheme added by the discourse addition unit 364. Since the answer sentence can be output, even if the answer contents for the user's utterance contents are not stored in the conversation database 500, the answer contents related to the user's utterance contents can be acquired, The output unit 600 can output a more humane answer sentence based on the answer sentence searched by the answer sentence search unit 370.
[0198]
Note that the discourse adding unit 364 is not limited to adding the other discourse range to the second morpheme information from which the morpheme has been deleted, but to the second morpheme information from which the morpheme has been deleted. (Stored in the database 500) may be added.
[0199]
(Sixth change example)
When the topic search unit 360 cannot search the second morpheme information including the first morpheme information from the second morpheme information, the topic search unit 360 collates the first morpheme information with each answer content, When the answer content including the first morpheme information can be searched from among the first morpheme information, the first search unit may acquire the second morpheme information associated with the searched answer content.
[0200]
Specifically, the topic search unit 360, to which the topic search command signal is input from the abbreviated sentence complement unit 350, based on the first morpheme information included in the input topic search command signal, If the second morpheme information that matches the first morpheme information cannot be obtained from each second morpheme information by collating with the morpheme information, as shown in FIG. The answer sentence associated with the second morpheme information is collated.
[0201]
When the topic search unit 360 determines that the morpheme constituting the first morpheme information (the action or the morpheme associated with the action) is included in the answer sentence by this collation, the answer sentence includes Search for associated second morpheme information.
[0202]
Thereby, even if the topic search unit 360 cannot search the second morpheme information that matches the first morpheme information from each second morpheme information, Since the answer sentence including the morpheme (action or the morpheme associated with the action) that constitutes the user can be identified and the second morpheme information associated with the identified answer sentence can be searched, the user's utterance content 2nd morpheme information corresponding to the 1st morpheme information which constitutes can be searched appropriately.
[0203]
As a result, since the topic search unit 360 can search for the optimal second morpheme information corresponding to the first morpheme information, the answer sentence search unit 370 can search for the optimal second morpheme information searched by the topic search unit 360. Based on the above, it is possible to acquire appropriate answer contents for the user's utterance contents.
[0204]
[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 in a general-purpose computer such as a personal computer.
[0205]
Here, as the programming language, in this embodiment, the topic requested by the user, the degree of emotion held for the user in a certain matter, or the type of statement, affirmative sentence, question sentence, repulsive sentence, etc. Languages that are hierarchically stored in a database in association with morphemes, for example, DKML (Discourse Knowledge Markup Language), XML (eXtensible Markup Language), C language, etc., developed by the inventors.
[0206]
That is, the conversation control device 1 stores data stored in each of the conversation databases 500a to 500d (stored information such as second morpheme information, fixed content, answer sentence, answer type, set group, discourse range, element information, etc.), etc. These parts can be constructed by DKML (Discourse Knowledge Markup Language) or the like, and a program for using the constructed storage information or the like can be executed.
[0207]
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 associated with the analyzed semantic content. A conversation control device, a conversation control system, and a conversation control method that have the effect of being able to output the optimum answer contents corresponding to the user's utterance contents by outputting the answer contents prepared in advance. It can be easily realized by a general purpose computer.
[0208]
In addition, since the developer who develops the conversation control device 1 can hierarchically construct the second morpheme information and the like for searching the answer contents for the user's utterance contents using the language in the database. The conversation control device 1 can acquire the response content for the utterance content from the database through a hierarchical procedure based on the utterance content of the user.
[0209]
In other words, the conversation control device 1 has determined and determined the hierarchy of the user's utterance content (for example, whether the second morpheme information stored in the database is in a higher concept or a lower concept). Appropriate answer contents can be acquired from the answer contents accumulated in advance based on the hierarchy.
[0210]
For this reason, the conversation control device 1 does not collate the first morpheme information composed of the user's utterance content and the previously stored “all” second morpheme information one by one. Since the second morpheme information and the first morpheme information may be collated, the second morpheme information approximate to the first morpheme information can be acquired in a short time.
[0211]
Furthermore, communication between the communication unit 800 and the communication unit 900 may be performed by transmitting and receiving data via a 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 suitable for the user's utterance content through the communication network 1000 according to the convention such as DKML. It is possible to retrieve the answer contents (described in DKML or the like) and obtain the retrieved answer contents (see FIG. 20).
[0212]
The program can be recorded on a recording medium. As shown in FIG. 23, examples of the recording medium include a hard disk 1100, a flexible disk 1200, a compact disk 1300, an IC chip 1400, and a cassette tape 1500. According to the recording medium on which such a program is recorded, the program can be easily stored, transported, sold, and the like.
[0213]
[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 this embodiment. As shown in the figure, the information processing system is substantially the same as the internal structure of 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). It is different in having. Since it is the same as the structure of 1st embodiment and a modified example except this difference, description about structures other than a difference is abbreviate | omitted.
[0214]
In the first embodiment, the conversation control device 1 has been described with respect to the process of acquiring the optimum answer sentence corresponding to the input information based on the input information from the user. A description will be given of a process in which the ranking unit 380 ranks the emotion level and the like of the user based on the input information from the user. The specific explanation is as follows.
[0215]
The ranking unit 380 ranks the degree of emotion held for the user based on the input information input from the user. In the present embodiment, as shown in FIG. A unit 381, an understanding state determination unit 382, and a conflict state determination unit 383. Here, the emotion level means the level of emotion that the conversation control apparatus 1 has for the input information. In the present embodiment, this emotion level is uniquely determined by an emotion state determination unit 381 described later based on the input information.
[0216]
The ranking unit 380 determines the degree of emotion held by the user based on the “Discourse Event” table stored in the discourse database. Here, as shown in FIG. 25, the “discourse event” table includes a cohesion factor (cohere) indicating that the first morpheme information is a factor having relevance (cohesion) with the discourse range, as shown in FIG. It consists of a topic change (shift) indicating that the first morpheme information is a factor that is not related to the current discourse range.
[0217]
Specifically, as shown in FIG. 26, the binding factor includes a binding factor (−) and a binding factor (+) in the present embodiment. In the cohesive factor (−), as shown in the figure, the topic search unit 360 searches the topic title associated with “low emotional level” belonging to the first discourse range in which the first morpheme information belongs to the previous discourse range. Means that. Here, “low emotion level” means that the conversation control device 1 sets a low emotion level for the topic title (for example, when the conversation control device 1 is not very interested in the topic title). Means that
[0218]
In the cohesive factor (+), as shown in the figure, the topic search unit 360 searches for the topic title associated with the “high emotion level” belonging to the first discourse range in which the first morpheme information belongs. Means that. Here, “high emotion level” means that the conversation control device 1 sets a high emotion level for the topic title (for example, when the conversation control device 1 is interested in the topic title). Means that.
[0219]
As shown in FIG. 26, these binding factors (−) and (+) are ranked based on the result of the “conditional” return processing by the return determination unit 330 and the result of the abbreviated sentence complement processing by the abbreviated sentence complement unit 350. Part 380.
[0220]
Moreover, the topic change is made up of topic change (−) and topic change (+) as shown in FIG. The topic change (−) means that the current topic title searched by the topic search unit 360 is changed to another topic title associated with “low emotion level” later, as shown in FIG. .
[0221]
The topic change (+) means that the current topic title searched by the topic search unit 360 is later changed to another topic title associated with “high emotion level” as shown in FIG. . These topic changes (−) (+) are determined by the ranking unit 380 based on the search results of the talk range by the talk range determination unit 340, as shown in FIG.
[0222]
In addition to the above, the “Discourse Scope Event” table has an interrupt factor indicating that the first morpheme information interrupts the current topic, and the first morpheme information is more difficult than the second morpheme information. This is composed of a difficult factor (harass) indicating that the first morpheme information is a conflicting factor (oppose) indicating that the first morpheme information is a conflicting factor with respect to the second morpheme information.
[0223]
As illustrated in FIG. 24, the interruption factor is determined by the ranking unit 380 based on the turn-back process performed by the turn-up determination unit 330 and the reflective process performed by the reflective determination unit 320. The difficult 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.
[0224]
The emotion state determination unit 381 ranks according to the frequency with which the second morpheme information including the first morpheme information is searched from each second morpheme information based on the search result by the topic search unit 360. It is a ranking means.
[0225]
The emotion state determination unit 381 is also a ranking unit that ranks a lower rank when the frequency of search is low, and ranks a higher rank when the frequency of search is high. The magnitude of this rank can be expressed as the degree of emotion held for the user, the degree of understanding of the input information, and the degree of confrontation felt with the user.
[0226]
In the present embodiment, the emotion level determined by the emotion state determination unit 381 can be ranked in six levels as shown in FIG. This emotion level is positioned in a direction in which the numerical value shown in the figure increases as the emotion level held by the user increases (in a better direction).
[0227]
Therefore, when the emotion level transitions from e (0) to e (3), it means that the emotion level held for the user increases. On the other hand, when the emotion level transitions from e (0) to e (-2), it means that the emotion level held for the user is lowered. Of the six levels, the reference emotion level is e (0) in the present embodiment.
[0228]
In the present embodiment, the ranking of the emotion level is performed using an emotion minus factor, an emotion plus factor, and topic change (+) (−). In this embodiment, this negative emotion factor is assumed to be the above-described interruption factor, difficult factor, conflict factor, cohesion factor (-), and topic change (-). The emotion plus factor consists of a cohesion factor (+) and a topic change (+).
[0229]
In the figure, the topic level (-) (+) changes the emotion level by two or more levels. This indicates that the current topic title is “Emotion level” is very “low” or “Emotion level” is very high. When a topic title associated with “high” is selected, the emotion level is changed in two or more stages.
[0230]
Specifically, when the second morpheme information including the first morpheme information is not searched by the topic search unit 360, the emotion state determination unit 381 ranks the emotion level held by the user to a lower rank.
[0231]
That is, the fact that the second morpheme information including the first morpheme information is not searched by the topic search unit 360 means that each of the second morpheme information in which the first morpheme information constituting the input information input from the user is stored in advance. Therefore, the emotional state determination unit 381 has the input information (first morpheme information) input from the user as an emotion negative factor (difficult factor). And set the emotion level for the user to be lower.
[0232]
On the other hand, when the second morpheme information including the first morpheme information is searched by the topic search unit 360, the emotion state determination unit 381 ranks the emotion level held for the user in a high rank.
[0233]
That is, the fact that the second morpheme information including the first morpheme information is searched by the topic search unit 360 means that each second morpheme in which the first morpheme information constituting the input information input from the user is stored in advance is stored. Since it can be determined that it is easier than information, the emotional state determination unit 381 determines that the input information input from the user can be understood, and the emotional level held by the user Set to higher.
[0234]
The emotional state determination unit 381 is also a ranking unit that ranks based on the determination result by the conversation range determination unit 340 (relevance determination unit). In this embodiment, the discourse range determination unit 340 collates the first discourse range indicating the searched discourse range with the second discourse range indicating the searched discourse range, and the second discourse range is the first discourse range. Relevance determining means for determining whether or not there is an association with a range.
[0235]
Specifically, the emotion state determination unit 381 determines, for example, the degree of emotion that the user has for the user when the conversation range determination unit 340 determines that the second conversation range is not related to the first conversation range. Rank to a lower rank.
[0236]
That is, the fact that the second topic range is determined not to be related to the first topic range by the conversation range determination unit 340 means that the current conversation range (second conversation range) including the first morpheme information is the previous one. Since it can be determined in a pseudo manner that it is different from the discourse range (first discourse range) of (the contextual topic has no cohesive surname; this is also referred to as “topic change”), the emotional state determination unit 381, 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 an emotion minus factor (topic change ( -)), And the emotion level of the user is set to the lower level (see FIGS. 26 and 27).
[0237]
As a result, the topic change (−) indicates that the current conversation range is changed to another conversation range, and the first morpheme information belonging to the changed conversation range is content that is not interesting for the conversation control device 1. means.
[0238]
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 can be determined that it is an emotional plus factor (topic change (+)), and the emotional level held for the user can be set higher.
[0239]
As a result, 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 has interesting contents for the conversation control device 1. To do.
[0240]
On the other hand, if it is determined by the conversation range determination unit 340 that the second discourse range is related to the first discourse range, the emotion state determination unit 381 ranks the emotion level held by the user at a high rank, for example. Rank.
[0241]
In other words, the fact that the second topic range is determined to be related to the first topic range by the conversation range determination unit 340 means that the current conversation range (second conversation range) including the first morpheme information is the previous one. Since it can be determined in a pseudo manner that it is substantially the same as the discourse range (first discourse range) (contextual topics have cohesiveness), the emotional state determination unit 381 determines 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 emotion level held for the user is set higher (see FIGS. 26 and 27).
[0242]
Thus, the cohesion factor (+) is that the current conversation range is substantially the same as the previous conversation range, and the first morpheme information belonging to the current conversation range is interesting for the conversation control device 1. Means.
[0243]
In this case, when 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 can be determined that it is an emotion negative factor (cohesion factor (-)), and the emotion level held for the user can be set to be lower.
[0244]
As a result, the cohesion 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 for the conversation control device 1. It means that there is.
[0245]
The emotional state determination unit 381 is also a ranking unit that ranks the rank based on the result of adding the morphemes constituting the discourse range to the first morpheme information by the abbreviated sentence complementing unit 350.
[0246]
Specifically, the abbreviated sentence complementing unit 350 selects a morpheme from the attributes (subjects consisting of principals, target cases consisting of objectives, etc.) constituting the first morpheme information extracted by the sentence structure analysis unit 430. Search for attributes that are not included. Based on the searched attribute, the abbreviated sentence complementing unit 350 adds a morpheme constituting the discourse range searched by the discourse range determining unit 340 to the attribute.
[0247]
When the abbreviation complementing unit 350 adds the morpheme constituting the discourse range to the first morpheme information, the emotional state determination unit 381 ranks the emotional level held by the user to a higher rank.
[0248]
That is, the input information consisting of the first morpheme information in the abbreviated sentence complementing unit 350 is the input sentence consisting of the first morpheme information before the abbreviated sentence (when the discourse range is added to the first morpheme information) Means that the information is an abbreviated sentence), the user inputs input information belonging to the current discourse range on the assumption that it belongs to the current discourse range. Therefore, the input information input at this stage tends to be an abbreviated sentence in which the morpheme consisting of the current discourse range is omitted (for details, refer to the “abbreviated sentence in the first embodiment”). (See the supplement section 350 ").
[0249]
Therefore, when the abbreviated sentence complementing unit 350 determines that the first morpheme information is an abbreviated sentence, the emotional state determination unit 381 determines that the current discourse range is substantially the same as the previous discourse range. It is determined in a pseudo manner, and it is determined that the first morpheme information is a cohesive factor having relevance with the previous discourse range. In this case, if the cohesion factor is a cohesion factor (+), the emotional state determination unit 381 sets the emotion level held to the user to a higher level, and if the cohesion factor is a cohesion factor (−), It is possible to set the feeling of feeling toward the user to be lower.
[0250]
Furthermore, the emotional state determination unit 381 ranks according to the frequency with which the fixed content including the first morpheme information or the reversion element is searched based on the search result by the reflexive determination unit 320 or the reversion determination unit 330. It is also a ranking means. The reflexive determination unit 320 is a fixed form obtaining unit that collates the extracted first morpheme information with each fixed form content and searches for reflex element information including the first morpheme information from each fixed form content.
[0251]
Specifically, when the reflexive determination unit 320 searches for fixed content that matches the first morpheme information from the fixed content, the emotional state determination unit 381 ranks the emotion level held by the user at a low rank. Rank.
[0252]
That is, the fact that the fixed content that matches the first morpheme information is retrieved by the reflexive determination unit 320 means that the first morpheme information is an element (interrupt factor) for interrupting the current topic. Therefore, the emotion state determination unit 381 determines that the first morpheme information is an emotion negative factor (interruption factor), and sets the emotion level held to the user to the lower level (see FIG. 26, see FIG. 27). For example, when a user inputs “good morning” (standard content) that has nothing to do with the topic during the conversation, “good morning” becomes an interruption factor.
[0253]
Further, the return determination unit 330 is configured so that the current first morpheme information extracted by the morpheme extraction unit 410 is the past answer content extracted by the morpheme extraction unit 410 (the previous first morpheme information (return element) is Stored in the return element database 802).
[0254]
When the return determination unit 330 determines that the current first morpheme information is included in the past response content, the emotional state determination unit 381 returns the response to the past response content (the user answers The first morpheme information can be determined in a pseudo manner as a cause of interruption for interrupting the current topic.
[0255]
In this case, since the current first morpheme information is an emotion minus factor (interruption factor), the emotion state determination unit 381 sets the emotion level held for the user to the lower one. (See FIGS. 26 and 27).
[0256]
Further, the return determination unit 330 includes the current morpheme information extracted by the morpheme extraction unit 410 in the past first morpheme information (this past first morpheme information is stored in the return element database 802). The emotion state determination unit 381 includes the current first morpheme information in the past first morpheme information, so that the user is the same as the past input information regardless of the current topic. It can be determined that the input information is repeatedly input.
[0257]
In this case, the emotional state determination unit 381 determines that the input information repeatedly input is an interruption factor, and sets the emotion level held for the user to the lower one (details are given in the first embodiment). (See “Turning process” in
[0258]
When the reversal determination unit 330 or the reflexive determination unit 320 cannot retrieve the fixed content that matches the first morpheme information from the fixed content, the emotional state determination unit 381 determines the emotion level held by the user. May be ranked higher.
[0259]
Furthermore, 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 emotion level held by the user to a lower rank. But there is.
[0260]
Here, the repulsion element means an element for the user to repel the response content output from the conversation control device 1, and in this embodiment, for example, the input information of the user is a response. It consists of a repulsive sentence indicating that it is a repulsive sentence with respect to the contents, a negative sentence indicating that the user input information is a negative sentence with respect to the response contents, and the like.
[0261]
That is, the fact that the input type of the input information input from the user is specified by the utterance type determination unit 440 as being composed of repulsive elements means that the user and the conversation control device 1 oppose each other. Therefore, the emotional state determination unit 381 determines that the first morpheme information is an emotion negative factor (conflict factor), and lowers the emotion level of the user. Setting is made (see FIGS. 26 and 27).
[0262]
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 harassed. It is a ranking means that judges that the cause is (difficult factor) and ranks the understanding level of the input information to a lower rank.
[0263]
That is, the fact that the second morpheme information including the first morpheme information is not searched 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 it can be determined, the understanding state determination unit 382 determines that the first morpheme information is a difficult factor, and sets the degree of understanding of the input information to a lower level.
[0264]
The understanding state determination unit 382 can easily input information input by the user when the topic search unit 360 searches for second morpheme information including the first morpheme information from each second morpheme information. It may be determined that the degree of understanding of the input information is ranked higher. In addition, when the first morpheme information is a factor that changes the topic to the binding factor, the understanding state determination unit 382 may rank the understanding level of the input information in a higher rank.
[0265]
Here, the degree of understanding means the degree of understanding of the input information input from the user. As shown in FIG. 28, the degree of understanding can be ranked in four levels in this embodiment.
[0266]
The larger the numerical value (the direction from r (−2) to r (1)), the more the input information is understood (the direction in which the understanding is clearly extended). On the other hand, the smaller the numerical value (from r (1) to r (-2)), the more the input information is understood (the direction in which the understanding is unclear).
[0267]
Specifically, as shown in the figure, when the understanding state determination unit 382 determines that the first morpheme information is a difficult factor based on r (0), the understanding state is shifted to a lower level ( If the first morpheme information is determined to be a factor that changes the topic to a cohesive factor, the degree of understanding is shifted to a higher direction.
[0268]
When the understanding state determination unit 382 determines that the first morpheme information is an interruption factor or a conflict factor, the first morpheme information does not contribute to the understanding of the input information. Maintain the current status (see the figure). Furthermore, the understanding state determination unit 382 changes the rank of understanding level to a higher rank when the feeling level changes in a positive direction.
[0269]
In addition, since a difficult factor, a cohesion factor, a topic change, a discontinuation factor, and a conflict factor are the same as the content demonstrated in the term of the said emotion state determination part 381, this description is abbreviate | omitted.
[0270]
When the input information specified by the utterance type determination unit 440 is a repulsion element (oppose; also referred to as a conflict factor), the conflict state determination unit 383 ranks the user with a high degree of conflict. Is ranked. In addition, the conflict state determination unit 383 ranks the degree of conflict with the user to a lower rank when the input information specified by the utterance type determination unit 440 is not a repulsion element such as a repulsion sentence. .
[0271]
Here, the degree of confrontation means the degree of confrontation that the conversation control device 1 has against the user. As shown in FIG. 29, this degree of confrontation can be ranked in five levels in this embodiment. The larger the value, the lower the degree of confrontation with the user. On the other hand, the smaller the numerical value, the higher (stronger) the degree of confrontation with the user.
[0272]
Specifically, as shown in the figure, when the conflict state determination unit 383 determines that the first morpheme information is a conflict factor with O (0) as a reference, the conflict level transitions to a lower level ( (With rank). Also, when the conflict state determination unit 383 determines that the first morpheme information is not a conflict factor but a factor that changes the discourse to a cohesion factor (not a repulsion factor), the conflict state determination unit 383 shifts the conflict level to a higher one. .
[0273]
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 level (a weak level of conflict). it can. In addition, when the emotion level for the first morpheme information is set in a lower direction by the emotion status determination unit 381, the conflict state determination unit 383 may set the conflict level to a higher level (a higher level of conflict). it can.
[0274]
Further, the conflict state determination unit 383 determines that the rank of the conflict level remains the same because the first morpheme information is not repulsive to the response content when the first morpheme information is an interruption factor or a difficult factor. (See the figure).
[0275]
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 receives the input emotion level and understanding level. Display the degree and degree of confrontation.
[0276]
(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 this embodiment.
[0277]
As shown in the figure, first, the input unit 100 performs a step of acquiring input information input from a user (S201). And the morpheme extraction part 410 performs the step which extracts each morpheme which comprises input information based on the input information acquired by the input part 100 (S202).
[0278]
Thereafter, the sentence structure analysis unit 430 performs a step of grouping 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 assumed to be first morpheme information.
[0279]
Next, the reflective determination unit 320 performs a step of performing reflective processing based on the first morpheme information specified by the sentence structure analysis unit 430 (S204, S205). Then, the reversal determination unit 330 performs a reversal process or a conditional reversal process based on the first morpheme information specified by the sentence structure analysis unit 430 (S206).
[0280]
After that, the discourse range determination unit 340 compares the first morpheme information with each discourse range, and performs a step of searching for a discourse range including the first morpheme information from each discourse range (S207). Furthermore, when the input information including the first morpheme information is an abbreviated sentence, the abbreviated sentence complementing unit 350 performs a step of adding a morpheme including the discourse range to the first morpheme information (S208).
[0281]
Then, the topic search unit 360 collates the first morpheme information with each second morpheme information based on the identified first morpheme information or the first morpheme information to which the morpheme is added. A step of searching for second morpheme information including the first morpheme information is performed (S209). Since the specific processes of S201 to S208 are the same as the contents of the “conversation control method” described in the first embodiment, the details of these processes are omitted.
[0282]
Next, the emotional state determination unit 381 has an emotional degree to use based on the search results obtained by the reflexive determination unit 320, the reversal determination unit 330, the discourse range determination unit 340, the abbreviated sentence complement unit 350, or the topic search unit 360. The step of ranking is performed (S210). Specifically, when the second morpheme information including the first morpheme information is not searched by the topic search unit 360, the emotion state determination unit 381 ranks the emotion level held by the user to a lower rank.
[0283]
That is, the fact that the second morpheme information including the first morpheme information is not searched by the topic search unit 360 means that each of the second morpheme information in which the first morpheme information constituting the input information input from the user is stored in advance. Therefore, the emotional state determination unit 381 has the input information (first morpheme information) input from the user as an emotion negative factor (difficult factor). And set the emotion level for the user to be lower.
[0284]
On the other hand, when the second morpheme information including the first morpheme information is searched by the topic search unit 360, the emotion state determination unit 381 ranks the emotion level held for the user in a high rank.
[0285]
That is, the fact that the second morpheme information including the first morpheme information is searched by the topic search unit 360 means that each second morpheme in which the first morpheme information constituting the input information input from the user is stored in advance is stored. Since it can be determined that it is easier than information, the emotional state determination unit 381 determines that the input information input from the user can be understood, and the emotional level held by the user Set to higher.
[0286]
In addition, the emotional state determination unit 381 can also rank the emotion level held for the user based on the determination result by the conversation range determination unit 340. In the present embodiment, the discourse range determination unit 340 collates the first discourse range indicating the searched discourse range with the second discourse range indicating the searched discourse range, and the second discourse range is the first discourse range. It is determined whether or not there is an association with the range.
[0287]
Specifically, the emotion state determination unit 381 has a low feeling of feeling for the user when the conversation range determination unit 340 determines that the second conversation range is not related to the first conversation range. Rank to rank.
[0288]
That is, the fact that the second topic range is determined not to be related to the first topic range by the conversation range determination unit 340 means that the current conversation range (second conversation range) including the first morpheme information is the previous one. Since it can be determined in a pseudo manner that it is different from the discourse range (first discourse range) of (the contextual topic has no cohesive surname; this is also referred to as “topic change”), the emotional state determination unit 381, 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 an emotion minus factor (topic change ( -)), And the emotion level of the user is set to the lower level (see FIGS. 26 and 27).
[0289]
As a result, the topic change (−) indicates that the current conversation range is changed to another conversation range, and the first morpheme information belonging to the changed conversation range is content that is not interesting for the conversation control device 1. means.
[0290]
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 can be determined that it is an emotional plus factor (topic change (+)), and the emotional level held for the user can be set higher.
[0291]
As a result, 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 has interesting contents for the conversation control device 1. To do.
[0292]
On the other hand, the emotional state determination unit 381 ranks the emotion level held by the user in a high rank when the conversation range determination unit 340 determines that the second conversation range is related to the first conversation range. It is attached.
[0293]
In other words, the fact that the second topic range is determined to be related to the first topic range by the conversation range determination unit 340 means that the current conversation range (second conversation range) including the first morpheme information is the previous one. Since it can be determined in a pseudo manner that it is substantially the same as the discourse range (first discourse range) (contextual topics have cohesiveness), the emotional state determination unit 381 determines 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 emotion level held for the user is set higher (see FIGS. 26 and 27).
[0294]
Thus, the cohesion factor (+) is that the current conversation range is substantially the same as the previous conversation range, and the first morpheme information belonging to the current conversation range is interesting for the conversation control device 1. Means.
[0295]
In this case, when 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 can be determined that it is an emotion negative factor (cohesion factor (-)), and the emotion level held for the user can be set to be lower.
[0296]
As a result, the cohesion 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 for the conversation control device 1. It means that there is.
[0297]
In addition, when the abbreviation complementing unit 350 adds the morpheme constituting the discourse range to the first morpheme information, the emotional state determination unit 381 ranks the emotion level held for the user to a higher rank. Can also be done.
[0298]
Specifically, the abbreviated sentence complementing unit 350 selects a morpheme from the attributes (subjects consisting of principals, target cases consisting of objectives, etc.) constituting the first morpheme information extracted by the sentence structure analysis unit 430. Search for attributes that are not included. Based on the searched attribute, the abbreviated sentence complementing unit 350 adds a morpheme constituting the discourse range searched by the discourse range determining unit 340 to the attribute. When the abbreviation complementing unit 350 adds the morpheme constituting the discourse range to the first morpheme information, the emotional state determination unit 381 ranks the emotional level held by the user to a higher rank.
[0299]
That is, the input information consisting of the first morpheme information in the abbreviated sentence complementing unit 350 is the input sentence consisting of the first morpheme information before the abbreviated sentence (when the discourse range is added to the first morpheme information) Means that the information is an abbreviated sentence), the user inputs input information belonging to the current discourse range on the assumption that it belongs to the current discourse range. Therefore, the input information input at this stage tends to be an abbreviated sentence in which the morpheme consisting of the current discourse range is omitted (for details, refer to the “abbreviated sentence in the first embodiment”). (See the supplement section 350 ").
[0300]
Therefore, when the abbreviated sentence complementing unit 350 determines that the first morpheme information is an abbreviated sentence, the emotional state determination unit 381 determines that the current discourse range is substantially the same as the previous discourse range. It is determined in a pseudo manner, and it is determined that the first morpheme information is a cohesive factor having relevance with the previous discourse range. In this case, if the cohesion factor is a cohesion factor (+), the emotional state determination unit 381 sets the emotion level held to the user to a higher level, and if the cohesion factor is a cohesion factor (−), It is possible to set the feeling of feeling toward the user to be lower.
[0301]
Furthermore, the emotional state determination unit 381 can also rank the emotion level held for the user based on the search result by the reflexive determination unit 320 or the reversion determination unit 330. The reflexive determination unit 320 is a fixed form obtaining unit that collates the extracted first morpheme information with each fixed form content, and searches for reflex element information including the first morpheme information from each fixed form content.
[0302]
Specifically, when the reflexive determination unit 320 searches for fixed content that matches the first morpheme information from the fixed content, the emotional state determination unit 381 ranks the emotion level held by the user at a low rank. Rank.
[0303]
That is, the fact that the fixed content that matches the first morpheme information is retrieved by the reflexive determination unit 320 means that the first morpheme information is an element (interrupt factor) for interrupting the current topic. Therefore, the emotion state determination unit 381 determines that the first morpheme information is an emotion negative factor (interruption factor), and sets the emotion level held to the user to the lower level (see FIG. 26, see FIG. 27). For example, when a user inputs “good morning” (standard content) that has nothing to do with the topic during the conversation, “good morning” becomes an interruption factor.
[0304]
Further, the return determination unit 330 is configured so that the current first morpheme information extracted by the morpheme extraction unit 410 is the past answer content extracted by the morpheme extraction unit 410 (the previous first morpheme information is the return element database 802). It is also determined whether it is included in
[0305]
When the reversal determination unit 330 determines that the current first morpheme information is included in the past response content, the emotional state determination unit 381 includes the current first morpheme information in the past response content. The user is reversing the past answer contents (the user is listening to the answer contents again), and the first morpheme information is pseudo-interrupt for interrupting the current topic Can be determined.
[0306]
In this case, since the current first morpheme information is an emotion minus factor (interruption factor), the emotion state determination unit 381 sets the emotion level held for the user to the lower one. (See FIGS. 26 and 27).
[0307]
Further, the return determination unit 330 collates 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 has the same input information as the past input information regardless of the current topic. It can be determined that the input is simply repeated. In this case, the emotional state determination unit 381 sets the emotion level held for the user to the lower one because the input information repeatedly input is an interruption factor.
[0308]
In addition, when the reflexive determination unit 320 cannot retrieve the fixed content that matches the first morpheme information from the fixed content, the emotional state determination unit 381 ranks the emotion level held by the user to a higher rank. You may attach. If the return determination unit 330 cannot retrieve past first morpheme information or past answer contents that match the current first morpheme information, the emotional state determination unit 381 ranks the emotion level held by the user with a high rank. You may rank.
[0309]
Furthermore, 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 emotion level held by the user to a lower rank. Can also be done.
[0310]
That is, the fact that the input type of the input information input from the user is specified by the utterance type determination unit 440 as being composed of repulsive elements means that the user and the conversation control device 1 oppose each other. Therefore, the emotional state determination unit 381 determines that the first morpheme information is an emotion negative factor (conflict factor), and lowers the emotion level of the user. Setting is made (see FIGS. 26 and 27).
[0311]
Next, when the understanding state determination unit 382 does not search the second morpheme information including the first morpheme information from the second morpheme information by the topic search unit 360, the input information input from the user is difficult ( harass) (difficult factor), a step of ranking the degree of understanding of the input information to a lower rank is performed (S211).
[0312]
Specifically, when the second morpheme information including the first morpheme information is not searched from the second morpheme information by the topic search unit 360, the first morpheme information is more difficult than the second morpheme information. Since it can be determined in a pseudo manner, 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.
[0313]
The understanding state determination unit 382 can easily input information input by the user when the topic search unit 360 searches for second morpheme information including the first morpheme information from each second morpheme information. It may be determined that the degree of understanding of the input information is ranked higher. In addition, when the first morpheme information is a factor that changes the topic to the binding factor, the understanding state determination unit 382 may rank the understanding level of the input information in a higher rank.
[0314]
Next, when the confrontation state determination unit 383 determines that the input information specified by the utterance type determination unit 440 is a repulsion element (oppose; also called a confrontation factor) such as a repulsion sentence, the degree of confrontation with the user is determined. A step of ranking to a higher rank is performed (S212). In addition, when the input information specified by the utterance type determination unit 440 is not a repulsive element such as a repulsive sentence, the confrontation state determination unit 383 ranks the degree of confrontation with the user to a lower rank. .
[0315]
Thereafter, 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 receives the input emotion level. The step of displaying the degree of understanding and the degree of conflict is performed (S213).
[0316]
(Operations and effects of information processing system and information processing method)
According to the invention according to the present embodiment, the reflexive determination unit 320, the reversion determination unit 330, or the topic search unit 360 collates the first morpheme information with each second morpheme information, and each second morpheme information. The second morpheme information including the first morpheme information is searched from the second morpheme information, and the emotion state determination unit 381 searches the second morpheme information including the first morpheme information from each second morpheme information. Since it can rank according to the magnitude | size etc. which are held with respect to a user according to magnitude | size, the emotional state determination part 381 outputs as a feeling degree which holds the ranked magnitude | size with respect to a user, for example ( For example, the conversation control apparatus 1 can be used as a pseudo-identification of the emotion level held for the user.
[0317]
In addition, developers who develop information processing systems can easily rank, for example, as the emotion level based on the search history performed between the first morpheme information and each second morpheme information. It is no longer necessary to develop a complex algorithm or neural network to calculate the emotion level etc. held by the information processing system, and as a result, the development time for developing this system can be shortened. .
[0318]
The discourse range determination unit 340 has a relationship 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. And the emotional state determination unit 381 ranks the emotional level held by the user based on the result determined by the conversation range determination unit 340. Therefore, the emotional state determination unit 381 includes the first morpheme information. Can rank the feelings of the user more appropriately than the ranking of the feelings of the user based on the search results obtained by matching the second morpheme information with each other. it can.
[0319]
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 conclude that the input is inconsistent with respect to a certain topic. Can be set low (bad direction).
[0320]
On the other hand, if the second discourse range has relevance 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 determined that the input information is relevant, the user can conclude that the input is consistent with respect to a certain topic. It is possible to set the feeling of embrace high (good direction).
[0321]
Furthermore, when the abbreviation sentence morpheme is added to each attribute constituting the first morpheme information by the abbreviated sentence complement unit 350, the emotional state determination unit 381 is the abbreviated sentence. It can be determined that the user is inputting input information on the assumption of the previously searched discourse range.
[0322]
For this reason, when the first morpheme information consisting of input information is an abbreviated sentence, the emotional state determination unit 381 can determine that the input information is input based on the previously searched discourse range. So, the user can conclude that the input is consistent for a certain topic, and can set a high (good direction) feeling for the user. it can.
[0323]
Furthermore, the reflexive determination unit 320 collates the first morpheme information with each fixed content, searches the fixed content including the first morpheme information from each fixed content, and the emotional state determination unit 381 Since the degree of emotion held for the user is ranked based on the search result, the emotional state determination unit 381 determines, for example, that when the fixed content including the first morpheme information is searched, the user is in a certain topic. As a result, it is possible to determine in a pseudo manner that the input information for interrupting the user has been input, so that the feeling of feeling held for the user can be ranked at a low rank, and as a result, Can be ranked more appropriately.
[0324]
On the other hand, when the reflexive determination unit 320 cannot search for fixed content including the first morpheme information, the emotional state determination unit 381 inputs input information for interrupting a certain topic by the user. Since it can be determined that the current topic is answered seriously, it is possible to rank the user with a high level of emotion.
[0325]
Furthermore, when the utterance type determination unit 440 specifies an input type indicating the type of input information and the specified input type is a repulsion element such as a repulsion sentence, the emotional state determination unit 381 The emotion level held by the user can be ranked at a lower rank, and the emotion level held for the user can be ranked more appropriately.
[0326]
Furthermore, when the second morpheme information including the first morpheme information is not searched by the topic search unit 360, the understanding state determination unit 382 does not previously store the second morpheme information related to the first morpheme information. Therefore, it can be determined in a pseudo manner that the input information composed of the first morpheme information is more difficult than the sentence composed of the second morpheme information.
[0327]
For this reason, since the understanding state determination unit 382 cannot understand the input information including the first morpheme information, it is determined in a pseudo manner that the user has input that the meaning is unknown to a certain topic. The degree of understanding of the input information can be ranked to a lower rank.
[0328]
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 determine in a pseudo manner that what is understood is input, and it is possible to rank the understanding level of the input information in a high rank.
[0329]
Moreover, since the developer who develops the conversation control apparatus 1 can construct hierarchically the second morpheme information and the like for searching for the answer contents with respect 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 related to the first morpheme information based on the first morpheme information corresponding to the user input information through a hierarchical procedure.
[0330]
That is, the reflexive determination unit 320, the reversal determination unit 330, the discourse range determination unit 340, or the topic search unit 360 includes the first morpheme information hierarchy corresponding to the input information (for example, the second morpheme information stored in the database). On the other hand, it is possible to search for appropriate second morpheme information from each second morpheme information stored in advance based on the determined hierarchy. .
[0331]
For this reason, the reflexive determination unit 320, the reversal determination unit 330, the discourse range determination unit 340, or the topic search unit 360 includes the first morpheme information composed of user input information and the pre-stored “all” second. Without matching each morpheme information, each “specific” second morpheme information that belongs to a specific hierarchy and the first morpheme information need to be collated, so the second morpheme information that approximates the first morpheme information Searches can be performed in a short time, and the results can be ranked in a short time based on the search results, such as the degree of emotion held for the user.
[0332]
Furthermore, when the reversal determination unit 330 collates the current first morpheme information with the past response content and determines that the current first morpheme information is included in the past response content, the emotional state determination unit 381 Can be determined in a pseudo manner that the user is turning back with respect to the past response content (that the user is listening to the response content again).
[0333]
In this case, the emotional state determination unit 381 artificially concludes that the user has input input information for interrupting a certain topic because the user is turning over the past answer contents. It is possible to rank the emotion level held for the user to a lower rank, and as a result, the emotion level held for the user can be more appropriately ranked.
[0334]
Finally, the reversal determination unit 330 collates the current first morpheme information with the past first morpheme information, and when the current first morpheme information is included in the past first morpheme information, the emotion state determination The unit 381 can determine in a pseudo manner that the input information simply input by the user in the past is re-input regardless of the answer content from the conversation control device 1.
[0335]
In this case, the emotional state determination unit 381 has nothing to do with the response content from the conversation control device 1 and the user simply inputs the same input information as the previous input information repeatedly. The emotion level held for the user can be ranked to a lower rank, and as a result, the emotion level held for the user can be more appropriately ranked.
[0336]
[Third embodiment]
(Basic configuration of face image display device)
Embodiments of the present invention will be described with reference to the drawings. FIG. 31 is a schematic configuration diagram showing a face image display device according to the present embodiment. As shown in the figure, the face image device according to the present embodiment is substantially the same as the internal structure of the conversation control device 1 (information processing device) in the second embodiment, but the face image acquisition unit 371 and the face image It differs in that it has a database 501. Since it is the same as the structure of 1st embodiment, a modified example, and 2nd embodiment except this different point, description about structures other than a different point is abbreviate | omitted.
[0337]
In the present embodiment, the ranking unit 380 (emotion state determination unit 381, understanding state determination unit 382, conflict state determination unit 383) holds the user based on input information such as voice input from the user. Although the process of ranking the emotion level and the like has been described, in the present embodiment, the face image acquisition unit 371 associates with the rank size based on the rank size ranked by the ranking unit 380. A process of acquiring the obtained face image and causing the output unit 600 to display the face image acquired by the face image acquisition unit 371 on the screen will be described. The specific explanation is as follows.
[0338]
Here, a plurality of face images are associated with codes such as characters and numerical values, and each face image is stored in the face image database 501 in advance. In the present embodiment, this sign means a numerical value. Specifically, in the present embodiment, as shown in FIG. 32, a correspondence table including codes, “facial image expressions”, and face images associated therewith is stored in the face image database 501.
[0339]
That is, as shown in the figure, each of the reference numerals 2 to -2 includes each "facial expression", for example, "excellent smile" / "smiling face" / "normal face" / "grimace" / “Fuzzy faces” are associated with each other, and images corresponding to these “facial image expressions” are stored in the face image database 501 as face images 1 to 5. In the present embodiment, each code shown in the figure has the same size as each rank ranked by the emotional state determination unit 381. The size of each code is the size of each rank. Is associated with each of the above.
[0340]
Similarly, as shown in FIG. 33, each of the reference numerals 1 to -2 includes each “facial expression”, for example, “good face” / “normal face” / “unfocused face” / “confused face”. Are associated with each other, and images corresponding to these “facial expressions” are stored in the face image database 501 as face images 11-14. In the present embodiment, each symbol shown in the figure has the same size as each rank ranked by the understanding state determination unit 382. The size of each symbol is the size of each rank. Is associated with each of the above.
[0341]
Similarly, as shown in FIG. 34, each of the reference numerals 2 to -2 includes a “facial expression”, for example, “very friendly face” / “friendly face” / “normal face”. / "Hostile face" / "Very hostile face" are associated with each other, and images corresponding to these "face image expressions" may be stored in the face image database 501 as face images 21-25. it can. In the present embodiment, each symbol shown in the figure has the same size as each rank ranked by the conflict state determination unit 383. The size of each symbol is the size of each rank. Is associated with each of the above.
[0342]
The face image acquisition unit 371 compares the rank with each code stored in advance based on the rank ranked by the ranking unit 380, and acquires the code that matches the rank from the codes. Code acquisition means. The face image acquisition unit 371 is also a display unit that displays on the screen a face image associated with the code based on the acquired code. Note that the ranking process is the same as the process described in the “ranking unit 380” in the second embodiment, and a detailed description thereof will be omitted.
[0343]
Specifically, in the present embodiment, the face image acquisition unit 371 to which the ranking signal is input from the emotion state determination unit 381 has, for example, an emotion level corresponding to the input ranking signal as illustrated in FIG. The rank (1) is compared with the codes 2 to -2 stored in the face image database 501, and the code (1) that matches the rank (1) of the emotion level from the codes 2 to -2. ) To get. The face image acquisition unit 371 that acquired the code (1) acquires the face image 2 associated with the code (1) based on the acquired code (1), and outputs the acquired face image 2 as an output unit. Output to 600.
[0344]
Similarly, in this embodiment, the face image acquisition unit 371 to which the ranking signal is input from the understanding state determination unit 382 has an understanding level corresponding to the input ranking signal, for example, as illustrated in FIG. The rank (1) and the codes 1 to -2 stored in the face image database 501 are collated, and the code (1) matching the rank (1) of the understanding level from the codes 1 to -2. ) To get. The face image acquisition unit 371 that acquired the code (1) acquires the face image 11 associated with the code (1) based on the acquired code (1), and outputs the acquired face image 11 to the output unit. Output to 600.
[0345]
Further, similarly, in the present embodiment, the face image acquisition unit 371 to which the ranking signal is input from the conflict state determination unit 383, as shown in FIG. 34, for example, the degree of conflict corresponding to the input ranking signal. Is compared with each code 2-2 stored in the face image database 501, and matches the rank (−1) of the degree of confrontation among the codes 2-2. The code (-1) is acquired.
[0346]
The face image acquisition unit 371 that acquired the code (−1) acquires the face image 24 associated with the code (−1) based on the acquired code (−1), and acquires the acquired face image 24. Is output to the output unit 600. The output unit 600 to which the face image is input from the face image acquisition unit 371 displays the input face image on the screen.
[0347]
Note that each face image stored in the face image database 501 is an image in which the expression composed of each part such as eyes and nose on the face changes continuously according to the size of each code as described above. Preferably there is. This face may be an animal face as well as a human face. Thereby, since the expression of each face image changes according to the size of each code, the output unit 600 can display the expression of the face image according to the rank on the screen, and the user can By looking at the face image displayed on the screen, the user can enjoy the feeling of talking with other users.
[0348]
(Face image display method using face image display device)
The face image display method by the face image display device having the above configuration can be implemented by the following procedure. FIG. 35 is a flowchart showing the procedure of the face image display method according to the present embodiment.
[0349]
As shown in the figure, first, the input unit 100 performs a step of acquiring the utterance content input from the user (S301). And the morpheme extraction part 410 performs the step which specifies the character string which comprises utterance content based on the utterance content acquired by the input part 100, and extracts each morpheme from the specified character string (S302, S303).
[0350]
Thereafter, the phrase analysis unit 420 performs a step of grouping 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 format is collectively referred to as first morpheme information. The processing of S301 to S304 is the same as the processing of S101 to S104 described in the first embodiment. For this reason, the detailed description about these processes is abbreviate | omitted.
[0351]
Next, the ranking unit 380 has an emotional degree or the like for use based on the search results by the reflexive determination unit 320, the reversal determination unit 330, the discourse range determination unit 340, the abbreviated sentence complement unit 350, or the topic search unit 360. Is ranked (S305). The processing in S305 is the same as the ranking processing described in the “information processing method” in the second embodiment, and thus detailed description thereof is omitted.
[0352]
Then, the face image acquisition unit 371 collates the rank with each code stored in advance based on the rank ranked by the ranking unit 380, and selects the code that matches the rank from the codes. Step to get. Thereafter, based on the acquired code, the face image acquisition unit 371 displays a face image associated with the code on the screen (S306).
[0353]
Specifically, in the present embodiment, the face image acquisition unit 371 to which the ranking signal is input from the emotion state determination unit 381 has, for example, an emotion level corresponding to the input ranking signal as illustrated in FIG. The rank (1) is compared with the codes 2 to -2 stored in the face image database 501, and the code (1) that matches the rank (1) of the emotion level from the codes 2 to -2. ) To get.
[0354]
The face image acquisition unit 371 that acquired the code (1) acquires the face image 2 associated with the code (1) based on the acquired code (1), and outputs the acquired face image 2 as an output unit. Output to 600. Here, the face image acquisition unit 371 to which the ranking signal is input from the understanding state determination unit 382 or the conflict state determination unit 383 performs the same processing as described above, and thus detailed description thereof is omitted.
[0355]
(Operation and effect of face image display device and face image display method)
According to the invention according to the present application, the face image acquisition unit 371 collates the rank ranked by the ranking unit 380 with each code stored in advance, and matches the rank from the codes. Since the face image associated with the sign can be displayed on the screen, the face image obtaining unit 371 assigns the rank ranked by the ranking unit 380 to the user. If the emotion level is held, the corresponding face image can be displayed on the screen according to the size of the emotion level.
[0356]
That is, since the face image acquisition unit 371 can switch the face image to be displayed on the screen according to the emotion level for the user, for example, if the currently ranked rank is the lowest, the lowest rank Can be displayed on the screen (for example, an image having a facial expression of an angry face).
[0357]
As a result, the expression of the face image displayed on the screen changes depending on the rank ranked by the ranking unit 380 as described above. Therefore, the user can change the facial color of other users. You can enjoy the real feeling of having a conversation while listening. Further, the user works hard toward the face image display device in order to raise the rank ranked by the face image display device, for example, to make the face image displayed on the screen “excellent smile”. This also leads to speaking, and as a result, boring time can be enjoyed by having a conversation with the face image display device.
[0358]
Furthermore, since the face image display device can output the ranked size as the emotion degree based on the search history performed between the first morpheme information and each second morpheme information, The developer who develops the image display device does not need to develop a complicated algorithm or neural network for causing the face image display device to calculate the degree of emotion held by the user. Development time for developing a device to achieve can be shortened.
[0359]
The second morpheme information including the first morpheme information includes not only the case where the second morpheme information includes the first morpheme information as it is, but the second morpheme information includes at least one morpheme constituting the first morpheme information. It also means a case.
[0360]
【The invention's effect】
As described above, according to the present invention, based on input information such as voice input from the user, a search is made for the response contents created in advance associated with the meaning contents grasped from the input information. Then, ranking is performed according to the frequency of the search, and the ranked size can be reflected in the facial image expression as the degree of emotion to the user. As a result, the user can experience a realistic feeling as if the user is having a conversation with another user.
[Brief description of the drawings]
FIG. 1 is a block diagram showing a schematic configuration of a conversation control device according to a first embodiment.
FIG. 2 is a block diagram showing an internal structure of a conversation control unit and a sentence analysis unit in the first embodiment.
FIG. 3 is a diagram showing the contents of each morpheme extracted by a morpheme extraction unit in 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 showing the contents of “case” specified by the sentence structure analysis unit in the first embodiment.
FIG. 6 is a diagram showing an “uttered sentence type” specified by an utterance type determining unit in 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 the contents of a hierarchical structure built inside the conversation database in the first embodiment.
FIG. 9 is a diagram showing a detailed relationship of a hierarchical structure built inside the conversation database in the first embodiment.
FIG. 10 is a diagram showing the content of a “topic title” built inside the conversation database in the first embodiment.
FIG. 11 is a diagram showing the content of “answer sentence type” associated with “topic title” built inside the conversation database in the first embodiment.
FIG. 12 is a diagram showing the contents of “topic title” and “answer text” belonging to “discourse range” built inside the conversation database in the first embodiment.
FIG. 13 is a diagram showing the contents of reflection element information stored in the reflection element database in the first embodiment.
FIG. 14 is a diagram showing the contents of a wrapping element and a morpheme of the wrapping element stored in the wrapping element database in the first embodiment.
FIG. 15 is a flowchart showing a processing procedure of the conversation control method according to the first embodiment.
FIG. 16 is a diagram showing utterance contents organized by a morpheme extraction unit in the first modification.
FIG. 17 is a diagram illustrating an internal configuration of a topic search unit in a second modified example.
FIG. 18 is a diagram illustrating a state in which the ratio calculation unit in the second modification collates each morpheme belonging to “case configuration” and each “topic title” for each “topic title”.
FIG. 19 is a diagram illustrating a state in which the ratio calculation unit in the second modified example collates each morpheme belonging to “each component” and each morpheme belonging to “topic title” for each “case”.
FIG. 20 is a diagram showing a schematic configuration of a conversation control system in a third modified example.
FIG. 21 is a diagram illustrating an internal configuration of a topic search unit in a sixth modified example.
FIG. 22 is a diagram illustrating a state in which the topic search unit in the sixth modification collates first morpheme information with second morpheme information or an answer sentence.
FIG. 23 is a diagram showing a recording medium for storing a program in the present embodiment.
FIG. 24 is a block diagram showing an internal structure of a conversation control unit and a sentence analysis unit in the second embodiment.
FIG. 25 is a diagram showing the contents of a “discourse event table” stored in the discourse event database in 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 showing the rank of emotion level determined by an emotion state determination unit in the second embodiment.
FIG. 28 is a diagram illustrating a rank of understanding level determined by an understanding state determination unit according to the second embodiment.
FIG. 29 is a diagram illustrating a rank of conflict levels determined by a conflict state determination unit according to the second embodiment.
FIG. 30 is a flowchart showing a processing procedure of a ranking method in the second embodiment.
FIG. 31 is a diagram showing a schematic configuration of a face image display device in a third embodiment.
FIG. 32 is a diagram showing the contents of a correspondence table stored in the face image database in the third embodiment (No. 1).
FIG. 33 is a diagram showing the contents of a correspondence table stored in the face image database in the third embodiment (No. 2).
FIG. 34 is a view showing the contents of a correspondence table stored in the face image database in the third embodiment (No. 3).
FIG. 35 is a flowchart showing a processing procedure of a face image display method in the third embodiment.
[Explanation of symbols]
DESCRIPTION OF SYMBOLS 1 ... Conversation control apparatus, 100 ... Input part, 200 ... Speech recognition part, 300 ... Conversation control part, 310 ... Management part, 320 ... Reflective determination part, 330 ... Determination part, 340 ... Discourse range determination part, 350 ... Omission Sentence complementing part, 360 ... topic searching part, 361 ... ratio calculating part, 362 ... selecting part, 363 ... deleting part, 364 ... discourse adding part, 370 ... answer sentence searching part, 371 ... face image obtaining part, 380 ... with ranking , 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 ... face image database, 600 ... output unit, 700 ... voice recognition dictionary storage unit, 8 0 ... communication unit, 801 ... reflective element database 802 ... Omugaeshi component database, 900 ... communication unit, 1000 ... communication network, 1100 ... hard disk 1200 ... flexible disk, 1300 ... compact disc, 1400 ... IC chip, 1500 ... Tape

Claims (12)

Face images made up of face images of humans, animals, etc. are respectively associated with codes such as characters and numerical values, and face image storage means for storing a plurality of face images in advance,
Character recognition means for identifying a character string indicating the input information based on input information such as voice input from a user;
Based on the character string specified by the character recognition means, morpheme extraction means for extracting at least one morpheme constituting the minimum unit of the character string as first morpheme information;
Morpheme storage means for storing in advance a plurality of second morpheme information indicating a morpheme consisting of one character, a plurality of character strings, or a combination thereof;
The first morpheme information extracted by the morpheme extraction unit and the second morpheme information are collated, 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, ranking is performed according to the frequency with which the second morpheme information including the first morpheme information is searched from the second morpheme information. Ranking means to
Code acquisition means for collating the rank with each code stored in advance based on the rank ranked by the ranking means, and acquiring the code matching the rank from the codes; ,
A face image display device comprising: display means for displaying the face image associated with the code on the screen based on the code acquired by the code acquisition means. The face image display device according to claim 1,
The ranking means ranks a low rank when the frequency of searching is low, and ranks a high rank when the frequency of searching is high. . The face image display device according to claim 1 or 2,
The ranking means outputs the ranked size as an understanding level for the input information. The face image display device according to claim 1 or 2,
The said ranking means outputs the magnitude | size rank | ranked as the feeling degree or confrontation degree which holds with respect to the said user, The face image display apparatus characterized by the above-mentioned. A face image formed of a face image of a human, an animal, or the like is associated with a code such as a character or a numerical value, and stores a plurality of the face images in advance.
Storing in advance a plurality of second morpheme information indicating a morpheme consisting of one character, a plurality of character strings, or a combination thereof;
Identifying a character string indicating the input information based on input information such as voice input from a user;
Extracting at least one morpheme constituting the minimum unit of the character string as first morpheme information based on the identified character string;
Collating the extracted first morpheme information with each second morpheme information, and searching the second morpheme information including the first morpheme information from the second morpheme information;
Based on the retrieved search results, the second morpheme information is ranked among the second morpheme information according to the frequency with which the second morpheme information including the first morpheme information is retrieved;
Collating the rank with each of the previously stored codes based on the ranked rank, and obtaining the code that matches the rank from the codes;
And displaying the face image associated with the code on the screen based on the acquired code. The face image display method according to claim 5,
A face image display method characterized by ranking a low rank when the frequency of searching is low and ranking a high rank when the frequency of searching is high. A face image display method according to any one of claims 5 and 6,
A face image display method characterized in that a rank of the ranked rank is used as an understanding level of the input information. A face image display method according to any one of claims 5 and 6,
A face image display method characterized in that the rank of the ranked rank is set as an emotion level or a confrontation level for the user. On the computer,
A face image formed of a face image of a human, an animal, or the like is associated with a code such as a character or a numerical value, and stores a plurality of the face images in advance.
Storing in advance a plurality of second morpheme information indicating a morpheme consisting of one character, a plurality of character strings, or a combination thereof;
Identifying a character string indicating the input information based on input information such as voice input from a user;
Extracting at least one morpheme constituting the minimum unit of the character string as first morpheme information based on the identified character string;
Collating the extracted first morpheme information with each second morpheme information, and searching the second morpheme information including the first morpheme information from the second morpheme information;
Based on the retrieved search results, the second morpheme information is ranked among the second morpheme information according to the frequency with which the second morpheme information including the first morpheme information is retrieved;
Collating the rank with each of the previously stored codes based on the ranked rank, and obtaining the code that matches the rank from the codes;
A program for executing a process including a step of displaying, on the screen, the face image associated with the code based on the acquired code. The program according to claim 9, wherein
A program for executing a process of ranking a low rank when the frequency to be searched is low and ranking a high rank when the frequency to be searched is high. A program according to any one of claims 9 and 10,
A program characterized in that a rank of the ranked rank is used as an understanding level for the input information. A program according to any one of claims 9 and 10,
A program characterized in that the rank of the ranked rank is the degree of emotion or confrontation held for the user.

Images