JP4751565B2 - Conversation control device, conversation control method, and program - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a conversation control apparatus, a conversation control method, and a program for searching for a title of a file related to input information based on input information input from a user.
[0002]
[Prior art]
In a conventional file management system, a file made up of characters, figures, etc. is stored in association with the title of the file. Thus, when searching for a file desired by the user, the user can refer to the title group corresponding to the file group, and thus can quickly acquire the corresponding file.
[0003]
In addition, when the number of titles increases, the user can classify the titles so that they have a superordinate concept or subordinate concept relationship. By referring to the classified titles, You can search quickly.
[0004]
[Problems to be solved by the invention]
However, when there are many title divisions, the user first refers to the title corresponding to the superordinate concept and then refers to the title corresponding to the subordinate concept, and thus reaches the corresponding title. It took a considerable amount of time.
[0005]
On the other hand, in recent years, there is a system that can search an input title from a plurality of titles by allowing the user to input a title desired by the user. Thus, the user can quickly search for a desired title without referring to each title having a relationship such as a superordinate concept.
[0006]
However, when a user constructs a plurality of titles so that they have a relationship of a superordinate concept or a subordinate concept, for example, a title “prior art” is constructed in a subordinate concept of a certain title, A subordinate concept may have a similar title “prior art”. In this case, when the user searches for the title “prior art”, if “prior art” is entered, multiple titles of the “prior art” will be searched, and the user desires “self” The title "prior art" could not be searched quickly.
[0007]
Therefore, the present application has been made in view of the above points, and identifies each morpheme that constitutes input information input from the user, and searches for a title such as a file related to the morpheme using the identified morpheme. It is an object of the present invention to provide a conversation control device, a conversation control method, and a program capable of more quickly searching for a title desired by a user.
[0008]
[Means for Solving the Problems]
The invention according to the present application has been made in order to solve the above-described problem, and includes any one morpheme that includes one character, a plurality of character strings, or a combination thereof and belongs to each attribute such as a subject case and a target case. Is stored in advance as second morpheme information, a plurality of titles including information data such as characters and figures or headings of the information data are stored in advance, and a character string indicating input information based on input information input by a user And at least one morpheme constituting the minimum unit of the character string is extracted as first morpheme information based on the specified character string, and the extracted first morpheme information and each second morpheme information are collated. From the second morpheme information, the second morpheme information including at least one morpheme constituting the first morpheme information is searched, and the second morpheme information is obtained based on the searched second morpheme information. Extracting morphemes belonging to one of the attributes to be formed, extracted collated with morphemes and each title from among the titles, characterized by searching a title that matches the morphemes.
[0009]
According to such an invention according to the present application, the conversation control device extracts morphemes belonging to any attribute constituting the second morpheme information based on the searched second morpheme information, and the extracted morpheme and each title Since the title that matches the morpheme can be searched from among the titles, the conversation control device is based on the searched second morpheme information (morpheme constituting the input information input by the user). Thus, a title related to the semantic content of the searched second morpheme information can be quickly searched from a plurality of topic titles.
[0010]
In addition, the conversation control device can specify the attribute of the morpheme constituting the searched second morpheme information, and use the morpheme belonging to the attribute to search for a title that matches the morpheme from each title. Therefore, if a morpheme belonging to the subject case attribute is used, a title related to the subject can be searched.
[0011]
  In the above configuration, the extracted first morpheme information and each second morpheme information are collated, and for each second morpheme information, the ratio of the first morpheme information to the second morpheme information is calculated. One second morpheme information is selected from each second morpheme information according to the size of each ratio calculated for each morpheme information, and the second morpheme information is selected based on the selected second morpheme information. A morpheme belonging to one of the constituent attributes is extracted, the extracted morpheme and each title are collated, and a title matching the morpheme is searched from each title. Also,The conversation control system further includes element storage means for previously storing a plurality of pieces of element information indicating an entire set group including a plurality of the morpheme sets in association with the set group, and the morpheme extraction means includes the The morpheme extracted from a character string is compared with each set group, the set group including the morpheme is selected from each set group, and the element information associated with the selected set group is Extracted as first morpheme information. In addition, a phrase analysis unit that summarizes in a phrase format based on the first morpheme information extracted by the morpheme extraction unit, and each morpheme of the first morpheme information that is summarized in a phrase format by the phrase analysis unit A sentence structure analyzing means for classifying the cases into cases. Further, each discourse range that is each morpheme of the second morpheme information is configured in a hierarchical structure including a relationship of a higher concept, a lower concept, a synonym, and an antonym with respect to another discourse range. .
[0012]
As a result, the conversation control device calculates the ratio of the first morpheme information to the second morpheme information for each second morpheme information, and according to the size of each ratio calculated for each second morpheme information. Since one second morpheme information can be selected from each second morpheme information, the conversation control device has, for example, a first morpheme information (an element constituting user input information) as the second morpheme information. If the second morpheme information with a large proportion of morpheme information can be acquired from a plurality of second morpheme information groups, the second morpheme information that follows the semantic space composed of the first morpheme information is more accurately obtained. As a result, by using the morpheme belonging to the second morpheme information, the file title desired by the user can be searched more accurately and quickly.
[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 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 replaced with “input sentence 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 character recognition means for specifying a character string corresponding to input information (other than speech) based on input information 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 acquires user input information (other than voice), specifies the acquired input information as a character string, and outputs the specified character string to the conversation control unit 300. 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 (a, i, e, e, etc.) corresponding to standard audio signals.
[0020]
The sentence analysis unit 400 analyzes the character string input to the conversation control unit 300. In this embodiment, as shown in FIG. 2, the morpheme extraction unit 410, the phrase analysis unit 420, the sentence structure, It has an 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, as first morpheme information, each morpheme constituting the minimum unit of the character string based on the character string specified by the speech recognition unit 200.
[0022]
Specifically, the morpheme extraction unit 410 to which a character string is input from the management unit 310 extracts each morpheme from the input character string. Here, in this embodiment, the morpheme means the minimum unit of the word configuration represented in the character string. As the minimum unit of the word configuration, for example, as shown in FIG. Part of speech such as adjectives and verbs. 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 including nouns, adjectives, verbs, and the like stored in advance in the morpheme database 450, and from among the character strings. Each morpheme (m1, m2,...) That matches the morpheme 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” (attribute).
[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 action / verb, time meaning time (consisting of tense, mood, aspect), location meaning location, etc. In the present embodiment, each morpheme associated with the “case” (case configuration) of the three elements of the subject, the object, and the action in the phrase is set 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 topic search unit 320.
[0033]
The utterance type determination unit 440 is a type specifying unit that specifies an utterance type indicating the type of utterance content 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” includes 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), rebound 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, Sentence elements related to the dictionary (see FIG. 7) are extracted. 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 a type for identifying the type of character string, and the sentence element in the present embodiment 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. By referring to the type of determination, the “spoken sentence type” can be determined (see FIG. 7).
[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 330 based on an instruction from the topic search unit 320 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. The conversation database 500 is also an answer storage unit that associates a plurality of answer contents with the second morpheme information, and stores in advance an answer type indicating the type of each answer content in association with each answer content. Furthermore, the conversation database 500 is composed of one character, a plurality of character strings, or a combination thereof, and stores a plurality of morpheme in advance as a second morpheme information, any one morpheme belonging to each attribute such as subject case and target case. It is also a means.
[0043]
As shown in FIG. 8, in this embodiment, the conversation database 500 is roughly divided into a discourse range (discourse) that means a relevance range for the content of the user's utterance, and a discourse range. It is composed of topics (topics) that mean a range that is most closely related to the content that the user utters. As shown in the figure, “discourse range” is positioned as a superordinate concept of “topic” in the present embodiment.
[0044]
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 antonym is clear in relation to other discourse ranges.
[0045]
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”. .
[0046]
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). .
[0047]
The topic title is not limited to each morpheme associated with the above three elements, but other “cases”, that is, a time meaning time (consisting of mood, tense, 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.
[0048]
In this embodiment, the topic title (second morpheme information) is stored in advance in the conversation database 500, and is distinguished from the first morpheme information (derived from the content spoken by the user). It is what is done.
[0049]
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".
[0050]
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.
[0051]
For example, {A What is a movie name? } Is converted into a topic title (subject; object; action). }, “A movie name” can be specified as the 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).
[0052]
The answer sentence means an answer sentence (answer contents) to be answered to the user. In this embodiment, the answer sentence is associated with each topic title (second morpheme information). It is stored in advance in the conversation database 500 (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 sentence (C; Condition), result sentence (E; Effect), time sentence (T; Time), location sentence (L; Location), negative sentence (N; Negation), positive sentence (A; Answer), question It shall be classified into a type (answer type) such as a sentence (Q).
[0053]
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.
[0054]
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 this order is the same below, the answer sentence 1-1 corresponding to the topic title 1-1 is (DA; statement affirmative sentence ("I also like Sato")), (IA ; Sentence affirmative sentence "I like Sato very much"), (CA; Condition affirmative sentence "Sato's home run is very impressive"), (EA; Result affirmative sentence "I always watch Sato's games on TV Masu "), (TA; time affirmative sentence" I actually like it from the five-batt continual refrain in Koshien "), (LA; place affirmative sentence" I like the serious face when standing on the batting " ), (NA; repulsion affirmation "I don't want to talk to people who don't like Sato, goodbye").
[0055]
In the present embodiment, the conversation control unit 300 includes a management unit 310, a topic search unit 320, and an answer sentence search unit 330, as shown in FIG.
[0056]
The management unit 310 controls the entire conversation control unit 300. Specifically, the management unit 310 to which a character string is input from the input unit 100 or the speech recognition unit 200 outputs the input character string to the morpheme extraction unit 410. Also, the management unit 310 outputs the answer sentence searched by the answer sentence search unit 330 to the output unit 600.
[0057]
The topic search unit 320 collates the first morpheme information extracted by the phrase analysis unit 420 with each second morpheme information (topic title), and forms at least the first morpheme information from each second morpheme information. It is the 1st search means which searches the 2nd morpheme information containing one morpheme. Specifically, the topic search unit 320 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, the first morpheme information and the conversation database 500. Is compared with the discourse range group stored in, and the discourse range related to the first morpheme information is searched from the discourse range group.
[0058]
For example, when each morpheme (first morpheme information) that belongs to the “case structure” constituting the utterance sentence uttered by the user is (Sato; *; I like) {I like Sato}, the topic search unit Since “Sato” is included in the “case composition”, 320 compares this “Sato” with the discourse range group, and searches for a discourse range (Sato) that matches “Sato”.
[0059]
Further, the topic search unit 320 that has selected the discourse range related to “case configuration” searches for the “topic title” closest to each morpheme belonging to “case configuration” from among the topic titles belonging to the selected discourse range. The search result is output as a search result signal to the answer sentence search unit 330 and the utterance type determination unit 440.
[0060]
For example, if the “case composition” of the utterance content is (Sato; *; I like) {I like Sato}, the topic search unit 320, as shown in FIG. The morpheme (Sato; *; I like) and the topic titles 1-1 to 1-4 belonging to the discourse range (Sato) are collated, and from each of the topic titles 1-1 to 1-4, “case composition” A topic title 1-1 (Sato; *; likes) that matches (or approximates) each morpheme belonging to (Sato; *; likes) is searched, and the search result signal 330 is used as a search result signal as a search result signal. Output to the utterance type determination unit 440.
[0061]
The utterance type determination unit 440 to which the search result signal is input from the topic search unit 320, based on the input search result signal, an answer search command for searching for a specific answer sentence that answers to the corresponding user. The signal (this answer search command signal includes the determined “sentence type”) is output to the answer sentence search unit 330.
[0062]
The answer sentence search unit 330 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 320. In addition, the answer sentence search unit 330 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 320, The answer type that matches the user's utterance type is searched from each answer type, and an answer sentence associated with the answer type is acquired based on the searched answer type (second search means, answer Acquisition means).
[0063]
Specifically, the answer sentence search unit 330, to which the search result signal from the topic search unit 320 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 “utterance sentence type” (utterance type) corresponding to the answer search command signal, from among the answer sentence groups (respective answer contents) associated with the topic title , Search for 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.)
[0064]
For example, if the topic title (second morpheme information) corresponding to the search result is the topic title 1-1 (Sato; *; I like) shown in FIG. The answer type that matches the “type of utterance” (for example, DA: utterance type) determined by the utterance type determination unit 440 from among the answer sentences 1-1 (DA, IA, CA, etc.) associated with 1 An answer sentence 1-1 consisting of (DA) (DA; (I also like Sato) is retrieved), and the retrieved answer sentence is output to the management unit 310 as an answer sentence signal.
[0065]
The management unit 310 to which the answer sentence signal is input from the answer sentence search unit 330 outputs the input answer sentence signal to the output unit 600. The output unit 600 is an output unit that outputs the answer sentence acquired by the answer sentence search unit 330. In the present embodiment, for example, a speaker, a display, and the like can be given. Specifically, the output unit 600 to which an answer sentence signal is input from the management unit 310 outputs an answer sentence {for example, I also like Sato} corresponding to the input answer sentence signal.
[0066]
(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. 13 is a flowchart showing the procedure of the conversation control method according to the present embodiment.
[0067]
First, the input unit 100 performs a step of acquiring the utterance content from the user (S100). 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.
[0068]
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.
[0069]
Next, the morpheme extraction unit 410 performs a step of extracting each morpheme constituting the minimum unit of the character string based on the character string specified by the speech recognition unit 200 (S103).
[0070]
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.
[0071]
Then, the phrase analysis unit 420 collects 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, as shown in FIG. 4, is based on each morpheme corresponding to the input extraction signal (for example, a dependency element of each morpheme (for example, Is extracted, and morphemes are grouped into clauses based on the extracted dependency elements. In the present embodiment, the first morpheme information means each morpheme belonging to one phrase.
[0072]
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.
[0073]
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”.
[0074]
That is, as shown in FIG. 5, the sentence structure analysis unit 430, for example, when the dependency element of each morpheme in the phrase is “or” or “is”, the morpheme before the dependency element is the subject. (Subject or subject). In addition, for example, when the dependency element of each morpheme in the phrase is “NO” or “NO”, the sentence structure analysis unit 430 determines that the morpheme before the dependency element is an object (target). To do.
[0075]
Further, for example, when the dependency element of each morpheme in the clause is “Yes”, the sentence structure analysis unit 430 determines that the morpheme before the dependency element is an action (predicate; It is determined.
[0076]
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 320.
[0077]
Next, the utterance type determination unit 440 performs a step of specifying an utterance type indicating the type of utterance content based on the phrase specified by the phrase analysis unit 420 (S106). Specifically, the utterance type determination unit 440 sets the “spoken sentence type” (utterance type) based on each morpheme corresponding to the sentence pattern signal input from the phrase analysis unit 420 and a phrase composed of each morpheme. judge.
[0078]
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” (utterance type) based on the extracted sentence elements.
[0079]
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 330 based on an instruction from the topic search unit 320 described later.
[0080]
Next, the topic search unit 320 collates the first morpheme information extracted by the phrase analysis unit 420 with each second morpheme information, and includes the morpheme constituting the first morpheme information from each second morpheme information. A step of searching for second morpheme information (topic title) is performed (S107).
[0081]
Specifically, the topic search unit 320 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, the first morpheme information and the conversation database 500. Is compared with the discourse range group stored in, and the discourse range related to the first morpheme information is searched from the discourse range group.
[0082]
For example, when each morpheme (first morpheme information) that belongs to the “case structure” constituting the utterance sentence uttered by the user is (Sato; *; I like) {I like Sato}, the topic search unit Since “Sato” is included in the “case composition”, 320 compares this “Sato” with the discourse range group, and searches for a discourse range (Sato) that matches “Sato”.
[0083]
Further, the topic search unit 320 that has selected the discourse range related to “case configuration” searches for the “topic title” closest to each morpheme belonging to “case configuration” from among the topic titles belonging to the selected discourse range. The search result is output as a search result signal to the answer sentence search unit 330 and the utterance type determination unit 440.
[0084]
For example, when “case composition” is (Sato; *; I like) {I like Sato}, the topic search unit 320, as shown in FIG. 12, each morpheme (Sato ; *; I like) and each topic title 1-1 to 1-4 belonging to the discourse range (Sato), and each morpheme belonging to “case composition” from among the topic titles 1-1 to 1-4 A topic title 1-1 (Sato; *; likes) that matches (or approximates) (Sato; *; likes) is searched, and the search result signal 330 is used as a search result signal and an utterance type determination unit. Output to 440.
[0085]
The utterance type determination unit 440, to which the search result signal is input from the topic search unit 320, based on the input search result signal, answers search command signal for causing the corresponding user to search for a specific answer sentence (this answer) The search command signal also includes the determined “sentence sentence type”) to the answer sentence search unit 330.
[0086]
Next, the answer sentence search unit 330, based on the second morpheme information (topic title) searched by the topic search unit 320, the identified utterance type of the user and each answer type associated with the second morpheme information, Are searched, a response type matching the user's utterance type is searched from among the response types, and an answer sentence associated with the searched response type is obtained (S108).
[0087]
Specifically, the answer sentence search unit 330 to which the search result signal is input from the topic search unit 320 and the answer search command signal is input from the utterance type determination unit 440 is the topic title (second second) corresponding to the input search result signal. Morphological information) and the “speech sentence type” (utterance type) corresponding to the answer search command signal, from the answer sentence group (each answer content) associated with the topic title, An answer sentence having an answer type (this answer type means "type of answer sentence" shown in FIG. 11) matching "type" (DA, IA, CA, etc.) is searched.
[0088]
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 330 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.
[0089]
Then, the management unit 310 to which the answer sentence signal is input from the answer sentence search unit 330 outputs the input answer sentence signal to the output unit 600. Thereafter, the output unit 600 to which the response sentence signal is input from the management unit 310 outputs an answer sentence {for example, I also like Sato} corresponding to the input response sentence signal (S109).
[0090]
(Operation and effect of conversation control device and conversation control method)
According to the invention according to the present application having the above-described configuration, the topic search unit 320 includes a second morpheme (element constituting the utterance content of the user) constituting the first morpheme information from the second morpheme information. Since the morpheme information is searched, and the answer content associated with the second morpheme information can be acquired based on the searched second morpheme information, the topic search unit 320 includes each morpheme constituting the utterance content of the user. Based on the meaning space (meaning grasped from the character string made up of each morpheme), the answer contents created in advance based on the meaning space can be obtained, It is possible to acquire the answer contents more suitable for the utterance contents than to obtain the answer contents associated with the keyword using the entire utterance contents as a keyword.
[0091]
Further, since the conversation control device 1 can search for the optimum answer content suitable for the user's utterance content based on each morpheme constituting the user's utterance content, development for developing the conversation control device 1 The user only needs to create the answer contents based on the semantic space constructed by each morpheme and the search function for searching the answer contents. Artificial intelligence and neural network to analyze the user's utterance contents There is no need to build a program consisting of a network or the like.
[0092]
Furthermore, since the topic search unit 320 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.
[0093]
Furthermore, the answer sentence search unit 330 searches the answer type (description, affirmation, location, repulsion, etc.) associated with each second morpheme information for an answer type that matches the user's utterance type, and performs a search. Since the answer contents associated with the answer type can be acquired based on the answer type, the answer sentence search unit 330 can utter the utterance types constituting the conversation contents of the user, for example, the user simply gives an opinion. Response content that matches the type of utterance from multiple response content based on what the user has, what the user has to say, what the user describes the location element, etc. A more optimal answer can be given to the corresponding user.
[0094]
(Example of change)
In addition, this invention is not limited to the said embodiment, The change as shown below can be added.
[0095]
(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.
[0096]
As shown in FIG. 14, some morphemes included in the character string uttered by the user are similar. For example, as shown in FIG. 14, if the element information indicating the entire group is “gift”, the “gift” is similar to a present, a gift, a year-end gift, a mid-year gift, a celebration, etc. 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”.
[0097]
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. "Gift" can be replaced with "Gift".
[0098]
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.
[0099]
(Second modified example)
As shown in FIG. 15, in the present modification example, the topic search unit 320 may include a ratio calculation unit 321 and a selection unit 322.
[0100]
The ratio calculation unit 321 collates the first morpheme information extracted by the morpheme extraction unit 410 with each second morpheme information (topic title), and for each second morpheme information, the first morpheme information is compared with the first morpheme information. It is a calculation means for calculating the proportion of information.
[0101]
Specifically, the ratio calculation unit 321 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.
[0102]
For example, as shown in FIG. 15, when the first morpheme information constituting the utterance sentence uttered by the user is (Sato; *; I like) {I like Sato}, the ratio calculation unit 321 Each morpheme (Sato; *; I like) belonging to the “case composition” is matched with each morpheme (Sato; *; I like) included in the topic title. The ratio that each morpheme (Sato; *; I like) belonging to “composition” is included is calculated to be 100%. The ratio calculation unit 321 performs these calculations for each topic title, and outputs each calculated ratio to the selection unit 322 as a ratio signal.
[0103]
The selection unit 322 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 321 for each second morpheme information. .
[0104]
Specifically, the selection unit 322 to which the ratio signal is input from the ratio calculation unit 321 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. 16). The selection unit 322 that has selected a topic title with a high ratio outputs the selected topic title to the answer sentence search unit 330 and the utterance type determination unit 440 as a search result signal. The answer sentence search unit 330 acquires an answer sentence associated with the topic title based on the topic title selected by the selection unit 322.
[0105]
Thereby, the ratio calculation unit 321 calculates the ratio of the first morpheme information to the second morpheme information for each second morpheme information, and the selection unit 322 calculates each ratio calculated for each second morpheme information. Since one second morpheme information can be selected from each second morpheme information according to the size of the first morpheme information, the selection unit 322 configures, for example, the first morpheme information (the user's utterance content) If the second morpheme information having a large percentage of the second morpheme information can be acquired from a plurality of second morpheme information groups, the second morpheme follows the semantic space composed of the first morpheme information. Information can be acquired more accurately.
[0106]
As a result, the answer sentence search unit 330 can acquire the answer sentence associated with the second morpheme information based on the second morpheme information acquired by the selection unit 322. Can obtain the best answer sentence.
[0107]
Moreover, since the selection part 322 can select a topic title with a high ratio calculated by the ratio calculation part 321 from a plurality of topic titles, it 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”.
[0108]
As a result, since the selection unit 322 acquires topic titles closely related to “case configuration”, the developer who develops the conversation control apparatus 1 stores topic titles that completely match “case configuration” in the conversation database 500 one by one. Therefore, the capacity of the conversation database 500 can be reduced.
[0109]
The ratio calculation unit 321 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.
[0110]
Specifically, the ratio calculation unit 321 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. Morphemes of the first morpheme information belonging to "" and each morpheme belonging to "case" of the topic title consisting of the same "case" as "case structure" are collated, and the morphemes constituting each "case" are the same It is determined whether or not.
[0111]
For example, as illustrated in FIG. 17, when the “case” morpheme of “case configuration” is (dog; person; bite) {dog bites a person}, the ratio calculation unit 321 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%).
[0112]
If the element constituting the topic title is (person; dog; bite) {person bites the dog}, the ratio calculation unit 321 uses the same procedure as described above, and the morphemes belonging to the two cases are calculated. Since they are different, the degree of coincidence for each “case” between the morpheme constituting “case composition” and “topic title” is calculated to be 33% (see FIG. 17).
[0113]
The ratio calculation unit 321 that has calculated the ratio selects a topic title with a high ratio from each ratio, and outputs the selected topic title to the answer sentence search unit 330 and the utterance type determination unit 440 as a search result signal.
[0114]
As a result, the ratio calculation unit 321 displays each morpheme of the first morpheme information belonging to each classified “case configuration” (subject case, target case, etc.) and a pre-stored topic title for each “case”. Since the second morpheme information including each morpheme of the first morpheme information in at least one “case” can be searched from the topic titles, the ratio calculation unit 321 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”. The matching second morpheme information can be searched, and the reply content {"really?" Or "I don't know the meaning"} associated with the second morpheme information can be acquired.
[0115]
That is, since the ratio calculation unit 321 can identify utterance contents that are difficult to identify, for example, “a person bites a dog” and “a dog bites a person”, an answer that is more suitable for the identified utterance contents, For the former, for example, “Really?”, For the latter, for example, “Are you okay?”
[0116]
(Third change example)
As shown in FIG. 18, the present modification example is not limited to the above-described embodiment and each modification example, 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).
[0117]
Here, the communication network 1000 means a communication network that transmits and receives data. In the present embodiment, for example, the Internet is used.
[0118]
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.
[0119]
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.
[0120]
[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.
[0121]
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. The language for hierarchically storing in the database in association with the morpheme, for example, DKML (Discourse Knowledge Markup Language) developed by the present inventors, and other C languages.
[0122]
That is, the conversation control apparatus 1 stores data (stored information such as second morpheme information, answer text, answer type, set group, element information, etc.) stored in each of the conversation databases 500a to 500d, and other parts as DKML ( It can be realized by executing a program that uses the stored information and the like constructed by Discourse Knowledge Markup Language).
[0123]
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.
[0124]
Furthermore, communication between the communication unit 800 and the communication unit 900 may be performed by transmitting and receiving data using a protocol such as DKML via a communication network. Thereby, for example, when there is no answer content suitable for the user's utterance content in the conversation control device, 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 search for the response content (described in DKML or the like) and acquire the searched response content.
[0125]
The program can be recorded on a recording medium. 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, as shown in FIG. According to the recording medium on which such a program is recorded, the program can be easily stored, transported, sold, and the like.
[0126]
[Second Embodiment]
(Basic configuration of conversation control system)
A second embodiment of the present invention will be described with reference to the drawings. FIG. 20 is a diagram showing an internal structure of the conversation control system according to the present embodiment. As shown in the figure, the conversation control device 1 in the conversation control system is substantially the same as the internal structure of the conversation control device 1 in the first embodiment, but has a file search unit 340 instead of the answer sentence search unit 330. It is different in point. 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.
[0127]
In the first embodiment, the conversation control device 1 has been described with respect to the process of acquiring the optimum answer content corresponding to the input information based on the input information from the user. However, in the present embodiment, the conversation control device 1 The input information from the user is classified into attributes such as subject case, target case, etc., and morphemes belonging to one of the classified attributes are used to collate multiple file names with their morphemes. A process for acquiring a file name that matches the morpheme and outputting the acquired file name on the screen will be described. The specific explanation is as follows.
[0128]
The file search unit 340 extracts morphemes belonging to any attribute (one or more attributes) constituting the topic title based on the topic title searched by the topic search unit 320, and extracts the extracted morpheme, each file name, And searching for a file name matching the morpheme from the file names.
[0129]
Here, the conversation database 500 is a title storage unit that stores in advance a plurality of titles including information data such as characters and figures or headings of the information data (hereinafter, this title will be described as “file name”). In the present embodiment, as shown in FIG. 21, the name is associated with the name indicating the size of the file, the date and time when the contents of the file are updated, and the like.
[0130]
Specifically, as shown in FIG. 21, for example, the topic title input from the topic search unit 320 is (I; B technology material; I want to see) {I want to see B technology material}. In this case, the file search unit 340 selects one attribute (for example, an object) from among the attributes constituting the topic title, and acquires a morpheme (B technology material) belonging to the selected attribute. The attribute to be selected may be a subject (subject) other than an object (target case) or an action (verb).
[0131]
The file search unit 340 that acquired the morpheme belonging to the attribute (object) collates the acquired morpheme with each file name (A technology material, B technology material, C technology material, D technology material,...). Then, a file name that matches the morpheme is acquired from each file name. The file search unit 340 outputs the acquired file name to the management unit 310, and the output unit 600 to which the file name is input from the management unit 310 displays the input file name on the screen.
[0132]
(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. The procedure until the topic title (second morpheme information) is acquired can be performed by the same procedure as the procedure (S101 to S107) in the first embodiment. Therefore, in the conversation control method described below, the flow after the topic title is acquired will be described.
[0133]
First, the file search unit 340 to which the topic title is input from the topic search unit 320 extracts morphemes that belong to any attribute that constitutes the input topic title and stores them in the extracted morpheme and conversation database 500. A step of collating a plurality of file names and obtaining a file name matching the morpheme from each file name is performed.
[0134]
For example, as shown in FIG. 21, when the topic title input from the topic search unit 320 is (I; B technology material; I want to see) {I want to see B technology material}, a file The search unit 340 selects one attribute (for example, an object) from among the attributes constituting the topic title, and acquires a morpheme (B-technology material) belonging to the selected attribute. This attribute selection may be a subject or action other than an object.
[0135]
After that, the file search unit 340 that acquired the morpheme belonging to the attribute (object), the acquired morpheme and each file name (A technology material, B technology material, C technology material, D technology material,...) And obtaining a file name that matches the morpheme from the file names. The file search unit 340 outputs the acquired file name to the management unit 310, and the output unit 600 to which the file name is input from the file search unit 340 displays the input file name on the screen.
[0136]
Note that the file search unit 340 extracts morphemes belonging to any of the attributes constituting the topic title based on the topic title selected by the selection unit 322, collates the extracted morpheme with each file name, A file name that matches the morpheme may be retrieved from the file names.
[0137]
Accordingly, the ratio calculation unit 321 calculates the ratio of the first morpheme information to the topic title for each topic title, and the selection unit 322 calculates the size of each ratio calculated for each topic title. Accordingly, since one topic title can be selected from each topic title, the selection unit 322 selects, for example, a plurality of topic titles having a large proportion of the first morpheme information in the topic title. If it can be acquired from the group, it is possible to more accurately acquire a topic title that follows the semantic space composed of the first morpheme information, and as a result, the file search unit 340 acquires a morpheme belonging to the topic title. Can be used to more accurately and quickly search for a file name desired by the user.
[0138]
(Operation and effect of conversation control device and conversation control method)
According to such an invention according to the present application, the file search unit 340 extracts morphemes belonging to any of the attributes constituting the topic title based on the searched topic title, and the extracted morpheme, each file name, , And the file name matching the morpheme can be searched from among the file names. Therefore, the file search unit 340 is searched from a plurality of file names based on the searched topic titles. The title related to the semantic content of the topic title can be searched quickly.
[0139]
In addition, the file search unit 340 can specify the attribute of the morpheme constituting the searched topic title, and use the morpheme belonging to the attribute to search for a file name that matches the morpheme from each file name. Therefore, for example, if a morpheme belonging to the attribute of the subject is used, only the file name related to the subject can be searched.
[0140]
【The invention's effect】
As described above, according to the present invention, by specifying each morpheme that constitutes the input information input from the user and searching for a title such as a file related to the morpheme using the specified morpheme, The title desired by the user can be searched more quickly.
[Brief description of the drawings]
FIG. 1 is a block diagram showing a schematic configuration of a conversation control system 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” constructed within 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 sentence” belonging to “discourse range” built inside the conversation database in the first embodiment.
FIG. 13 is a flowchart showing a procedure of a conversation control method according to the first embodiment.
FIG. 14 is a diagram showing utterance contents organized by a morpheme extraction unit in the first modification.
FIG. 15 is a diagram illustrating an internal configuration of a topic search unit in a second modified example.
FIG. 16 is a diagram illustrating a state in which the ratio calculation unit according to the second modification collates each morpheme belonging to “case configuration” and each “topic title” for each “topic title”.
FIG. 17 is a diagram illustrating a state in which the ratio calculation unit in the second modified example collates each morpheme belonging to “case configuration” and each morpheme belonging to “topic title” for each “case”.
FIG. 18 is a diagram showing a schematic configuration of a conversation control system in a third modified example.
FIG. 19 is a diagram showing a recording medium for storing a program in the first embodiment.
FIG. 20 is a block diagram showing a schematic configuration of a conversation control system according to a second embodiment.
FIG. 21 is a diagram showing a series of flow until the file search unit in the second embodiment acquires one file name from the conversation database.
[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 ... Topic search part, 321 ... Ratio calculation part, 322 ... Selection part, 330 ... Answer sentence search 340 ... file search unit 400 ... sentence analysis unit 410 ... morpheme extraction unit 420 ... sentence analysis unit 430 ... sentence structure analysis unit 440 ... speech type determination unit 450 ... morpheme database 460 ... speech type database 500 ... Conversation database 600 ... Output unit 700 ... Speech recognition dictionary storage unit 800 ... Communication unit 900 ... Communication unit 1000 ... Communication network 1100 ... Hard disk 1200 ... Flexible disk 1300 ... Compact disk 1400 ... IC chip, 1500 ... cassette tape

Claims (9)

A morpheme storage means that consists of one character, a plurality of character strings, or a combination thereof, and stores in advance a plurality of morphemes associated with each attribute of subject case, target case, and action as second morpheme information;
Title storage means for storing in advance a plurality of titles of files storing information data such as characters and graphics;
Character recognition means for identifying a character string indicating the input information based on the input information input by the 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;
A phrase analysis means for grouping into a phrase format based on the first morpheme information extracted by the morpheme extraction means;
Sentence structure analysis means for classifying each morpheme of the first morpheme information summarized in the phrase format by the phrase analysis means into subject case, target case, and action;
The first morpheme information extracted by the morpheme extraction unit and classified by the sentence structure analysis unit as subject case, target case, and action is compared with each second morpheme information, From the first search means for searching the second morpheme information including at least one morpheme constituting the first morpheme information,
Based on the second morpheme information searched by the first search means, the morpheme belonging to any attribute constituting the second morpheme information is extracted, and the extracted morpheme and each title are collated. , A conversation control device having second search means for searching for the title that matches the morpheme from the titles,
Further, the first search means collates the first morpheme information extracted by the morpheme extraction means and classified into subject case, target case and action by the sentence structure analysis means and each second morpheme information. Calculating means for calculating the ratio of the first morpheme information to the second morpheme information for each second morpheme information;
Selecting means for selecting one second morpheme information from the second morpheme information according to the size of each ratio calculated for each second morpheme information by the calculation unit; ,
The second search unit extracts the morpheme belonging to any attribute constituting the second morpheme information based on the second morpheme information selected by the selection unit, and the extracted morpheme and each title And searching for a title that matches the morpheme from each title. The conversation control device according to claim 1, further comprising element storage means for storing in advance a plurality of pieces of element information indicating an entire set group including a plurality of sets of the morphemes in association with the set group,
The morpheme extraction unit collates the morpheme extracted from the character string with each set group, selects the set group including the morpheme from the set groups, and associates the set group with the selected set group. The conversation control device is characterized in that the extracted element information is extracted as the first morpheme information. The conversation control apparatus according to claim 1 or 2 , wherein when the title is searched for by the second search means , a range in which each morpheme of the second morpheme information is related to a content spoken by a user. Whether or not it matches the title included in each discourse range , and the discourse range is a hierarchical structure consisting of a relationship between a higher concept, a lower concept, a synonym, and an antonym in relation to other discourse ranges A conversation control device characterized by being configured. A step of storing a plurality of each morpheme consisting of one character, a plurality of character strings, or a combination thereof and corresponding to each attribute of the subject case, the target case, and the action in the morpheme storage means in advance as second morpheme information ,
Storing a plurality of titles in advance in a title storage means for storing information data such as characters and graphics;
A step of identifying a character string indicating the input information based on the input information input from the user by the character recognition means;
Morpheme extraction means, based on the character string specified by the character recognition means, to extract at least one morpheme constituting the minimum unit of the character string as first morpheme information;
A step of analyzing the clauses based on the first morpheme information extracted by the morpheme extraction unit;
The sentence structure analyzing means classifies each morpheme of the first morpheme information collected in the phrase format by the phrase analyzing means into a subject case, a target case, and an action;
The first search means collates the first morpheme information extracted by the morpheme extraction means and classified into subject case, target case, and action by the sentence structure analysis means, and the second morpheme information, A first search step for searching the second morpheme information including at least one of the morphemes constituting the first morpheme information from second morpheme information;
Based on the second morpheme information searched by the first search unit, a second search unit extracts the morpheme belonging to any attribute constituting the second morpheme information, and the extracted morpheme and the A second search step of matching each title and searching for the title that matches the morpheme from the titles,
Furthermore, the first search step includes
The calculation means included in the first search means extracts the first morpheme information and the second morpheme information extracted by the morpheme extraction means and classified into subject case, target case and action by the sentence structure analysis unit. Collating and calculating, for each second morpheme information, the ratio of the first morpheme information to the second morpheme information;
The selection means included in the second search means is configured to select one of the second morpheme information from the second morpheme information according to the size of each ratio calculated for the second morpheme information by the calculation means. Selecting morpheme information,
The second search step includes
Based on the second morpheme information selected by the selection means, the morpheme belonging to any attribute that constitutes the second morpheme information is extracted, the extracted morpheme and each title are collated, and each title A method for controlling conversation of a computer, comprising: searching for a title that matches the morpheme. 5. The computer conversation control method according to claim 4 , further comprising a step of storing a plurality of pieces of element information indicating an entire set group including a plurality of sets of the morphemes in advance in an element storage unit in association with the set group. ,
The morpheme extraction unit collates the morpheme extracted from the character string with each set group, selects the set group including the morpheme from the set groups, and associates the set group with the selected set group. The extracted conversation information is extracted as the first morpheme information. 6. The conversation control method for a computer according to claim 4 or 5 , wherein when the title is searched by the second search means , each morpheme of the second morpheme information has a relevance with respect to a content spoken by a user. It is determined whether or not it matches the title included in each discourse range meaning a certain range, and the discourse range is composed of a relationship of a superordinate concept, a subordinate concept, a synonym, and an antonym with respect to another discourse range. A computer conversation control method comprising a hierarchical structure. On the computer,
Consisting of one character, a plurality of character strings, or a combination thereof, a step of storing a plurality of morphemes associated with each attribute of subject case, target case, and action in advance as second morpheme information;
Storing in advance a plurality of titles of files storing information data such as characters and graphics;
Identifying a character string indicating the input information based on the input information input by the user;
Extracting at least one morpheme constituting the minimum unit of the character string as first morpheme information based on the identified character string;
Summarizing in phrase form based on the extracted first morpheme information;
Classifying each morpheme of the first morpheme information grouped in clause form into subject case, target case, action,
The first morpheme information extracted and classified into subject case, target case, and action is compared with each second morpheme information, and at least the first morpheme information is configured from each second morpheme information Retrieving the second morpheme information including one of the morphemes;
Based on the searched second morpheme information, the morpheme belonging to any attribute that constitutes the second morpheme information is extracted, the extracted morpheme and each of the titles are collated, And a step of searching for the title that matches the morpheme,
Further, the computer compares the first morpheme information extracted and classified into subject case, target case, and action with each second morpheme information, and for each second morpheme information, the second morpheme information. Calculating a ratio of the first morpheme information to
Selecting one second morpheme information from the second morpheme information according to the size of each ratio calculated for each second morpheme information;
Based on the selected second morpheme information, extract the morpheme belonging to any attribute constituting the second morpheme information, collate the extracted morpheme and each title, from among each title, A program for executing a process including a step of searching for a title that matches the morpheme. The program according to claim 7 , wherein a plurality of pieces of element information indicating an entire set group including a plurality of sets of the morphemes are stored in advance in an element storage unit in association with the set group.
The morpheme extracted from the character string is compared with each set group, the set group including the morpheme is selected from the set groups, and the element information associated with the selected set group is obtained. A program for executing a process including a step of extracting as the first morpheme information. 9. The program according to claim 7 , wherein each morpheme in the second morpheme information is related to a content spoken by a user when searching for the title by the second search unit. It is determined whether or not it matches the title included in each discourse range , and the discourse range is configured in a hierarchical structure including a relationship between a higher concept, a lower concept, a synonym, and an antonym in relation to other discourse ranges. Program.

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