JP2015176099A - Dialog system construction assist system, method, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a dialog system construction assist system capable of constructing a scenario using a dialog between a user and operator and the action of the operator.SOLUTION: In a dialog system 100, an audio recognition unit 101 performs audio recognition on utterances contained in a dialog between a user and operator, and produces results of audio recognition including texts corresponding to the utterances. An intention understanding unit 102 understands the intentions of the utterances on the basis of the texts, and obtains result of intention understanding including types of utterances, intentions of the utterances, words, and meaning classes of teh words. A dialog information memory unit stores the results of audio recognition, the results of intention understanding, and actions which the operator has performed in relation to the dialog. A scenario construction unit 106 acquires as attributes words having meaning classes that are shared between an utterance of a question and an utterance of a response which are contained in the dialog, and uses the attributes and actions to construct a scenario.

Description

  Embodiments described herein relate generally to a dialogue system construction support apparatus, method, and program.

  There is an interactive system that automatically responds to a user's utterance such as an automatic voice response device. Such an interactive system responds according to a pre-built scenario. The interactive system may fail to respond because the scenario does not match the user's request. In that case, the operator responds to the user. A new scenario needs to be added to the dialog system so that it can respond well if a similar request is subsequently received.

  It is required that a scenario can be constructed from a dialogue between a user and an operator regarding a case where the dialogue system fails to respond. Cited Document 1 discloses an automated response system that performs learning using a conversation set between an agent and a user. However, there is no technique for constructing a scenario from a dialogue between a user and an operator in consideration of an action (behavior) performed by the operator during a response.

Patent No. 4901738

  The problem to be solved by the present invention is to provide a dialogue system construction support apparatus, method, and program capable of constructing a scenario from a dialogue between a user and an operator and an action of the operator.

  A dialogue system construction support apparatus according to an embodiment includes a voice recognition unit, an intention understanding unit, a dialogue information storage unit, and a scenario construction unit. The voice recognition unit performs voice recognition on a plurality of utterances included in the dialogue between the user and the operator, and generates a voice recognition result including a plurality of texts corresponding to each of the plurality of utterances. The intention understanding unit understands the intention of each of the plurality of utterances based on each of the plurality of texts, and each type of the plurality of utterances, each intention of the plurality of utterances, and words included in the plurality of texts And an intention understanding result including the meaning class of the word. The dialogue information storage unit stores the voice recognition result, the intention understanding result, and the action executed by the operator in relation to the dialogue in association with each other. The scenario construction unit obtains, as an attribute, a word having a semantic class common to the utterance of the question and the utterance of the answer included in the dialogue, and constructs a scenario using the attribute and the action.

1 is a block diagram schematically showing a dialogue system according to an embodiment. The flowchart which shows the example of a procedure of the dialog log recording which concerns on embodiment. The figure which shows an example of the dialogue between a user and an operator. The figure which shows the example of the kind of utterance. The figure which shows the example of an intention tag. The figure which shows the example of action. The figure which shows the example of a semantic class. The figure which shows the example of action content. The figure which shows the dialogue log regarding the dialogue shown in FIG. The flowchart which shows the example of a procedure of the scenario construction which concerns on embodiment. The figure which shows an example of the scenario constructed | assembled from the dialogue log shown in FIG. The figure which shows the other example of the scenario constructed | assembled from the dialogue log shown in FIG. The figure which is an example of a dialog with a user and an operator, Comprising: The figure which shows the example which a user utters other than an answer with respect to an operator's question. The figure which shows the evaluation data for the scenario construction part shown in FIG. 1 to evaluate a scenario. The flowchart which shows the example of a procedure of the action candidate display which concerns on embodiment. The figure which shows an example of the content which the dialog state display part shown in FIG. 1 displays.

  Hereinafter, embodiments will be described with reference to the drawings. Embodiments relate to an interactive system that automatically responds to a user's utterance. This dialogue system is used in, for example, a contact center. The dialogue system selects a scenario that matches the user's utterance from scenarios registered in advance (dialog scenarios), and responds according to the scenario. If the interactive system fails to respond, the operator responds through interaction with the user. The dialogue system can construct a new scenario based on the dialogue between the user and the operator and the action (action) of the operator. As a result, the interactive system can respond well if it subsequently receives a similar request. Furthermore, scenario construction costs can be reduced. In addition, the number of necessary operators can be reduced.

  FIG. 1 schematically shows an interactive system 100 according to the embodiment. As shown in FIG. 1, the dialogue system 100 includes a voice recognition unit 101, an intention understanding unit 102, a dialogue control unit 103, a response generation unit 104, a dialogue extraction unit 105, a scenario construction unit 106, a scenario update unit 107, and a dictionary storage. Unit 108, intention model storage unit 109, scenario storage unit 110, dialog log storage unit (also referred to as dialog information storage unit) 111, dialog state display unit 112, scenario search unit 113, and scenario object database (DB) 114.

  First, the automatic response process of the interactive system 100 will be briefly described. In one example, the user communicates with the interactive system 100 via a network using a terminal such as a mobile phone or a smartphone. The interactive system 100 provides a service to a terminal via a network by automatic response processing. For example, the interactive system 100 transmits map data indicating the user's destination to the terminal, as in an example described later.

  The dialogue system 100 executes automatic response processing using the voice recognition unit 101, the intention understanding unit 102, the dialogue control unit 103, the response generation unit 104, the dictionary storage unit 108, the intention model storage unit 109, and the scenario object DB 114. . The voice recognition unit 101 performs voice recognition on a user's utterance and generates a natural language text (hereinafter simply referred to as text) corresponding to the utterance. The intention understanding unit 102 analyzes the text with reference to the dictionary storage unit 108 and the intention model storage unit 109 to understand the intention of the utterance, and outputs an intention understanding result. The dialogue control unit 103 selects a scenario corresponding to the intention understanding result from the scenario object DB 114, and executes an action (for example, transmission of map data) defined in the selected scenario. The response generation unit 104 generates a response sentence corresponding to the action executed by the dialogue control unit 103. The response sentence is converted into voice by a voice synthesis technique and output.

Next, scenario construction processing of the interactive system 100 will be described.
In the dialog system 100, the dialog with the user may fail due to a reason that a scenario that matches the user's request does not exist in the scenario object DB 114. When the dialogue with the user fails, the dialogue control unit 103 transfers the connection with the user to the operator. Furthermore, even when a prescribed condition occurs during the response, the dialogue control unit 103 can transfer the connection with the user to the operator. Thereby, the dialogue between the operator and the user starts.

  The dialogue system 100 analyzes the dialogue between the user and the operator. The dialogue system 100 constructs a new scenario based on the analysis result so that it can respond well when a similar request is subsequently received. For scenario construction processing, the speech recognition unit 101, intention understanding unit 102, dialogue extraction unit 105, scenario construction unit 106, scenario update unit 107, dictionary storage unit 108, intention model storage unit 109, scenario storage unit 110, dialogue log storage The unit 111, the dialog state display unit 112, and the scenario search unit 113 are used. A part including these elements related to the scenario construction process is referred to as a dialogue system construction support unit. As shown in FIG. 1, the dialogue system construction support unit may be incorporated in the dialogue system 100 or may be provided outside the dialogue system 100. When the dialogue system construction support unit is incorporated in the dialogue system 100, the voice recognition unit 101, the intention understanding unit 102, the dictionary storage unit 108, and the intention model storage unit 109 are shared in the automatic response process and the scenario construction process. Can do.

  The voice recognition unit 101 performs voice recognition on a plurality of utterances included in the utterance between the user and the operator, and generates a plurality of texts corresponding to each of the plurality of utterances. That is, the voice recognition unit 101 converts a plurality of utterances into a plurality of texts by a voice recognition technique.

  The intention understanding unit 102 understands the intention of the utterance corresponding to the text based on each text generated by the speech recognition unit 101. Specifically, the intention understanding unit 102 performs morphological analysis on the text to decompose the text into words in morpheme units. Subsequently, the intent understanding unit 102 refers to the dictionary stored in the dictionary storage unit 108 and uses the proper expression extraction technique to determine the meaning of the word for each of the noun, proper noun, verb, and unknown word. Assign a semantic class to represent. In the dictionary, a plurality of words are registered in association with semantic classes.

  The intention understanding unit 102 understands the intention of the utterance by referring to the intention model stored in the intention model storage unit 109 using the features such as the morpheme, the semantic class of the word, the notation of the word, and the like. Output. The intention model is generated in advance from a large number of utterance samples by learning using semantic classes and words as features. The method of understanding the intention is not limited to the example described here.

  The dialogue extraction unit 105 receives the intention understanding result from the intention understanding unit 102, and detects an operation performed on the dialogue system 100 by the operator during the response as an action of the operator. The action detection can be based on information received from a computer terminal operated by the operator. Specifically, the dialogue extraction unit 105 can receive information indicating the content of the action executed by the operator from the computer terminal. The dialogue extraction unit 105 records the analysis result of the dialogue between the user and the operator and the action of the operator in the dialogue log storage unit 111 in association with each other. The analysis result of the dialogue includes a voice recognition result and an intention understanding result regarding the user's utterance, and a voice recognition result and an intention understanding result regarding the operator's utterance.

  The scenario construction unit 106 constructs a scenario with reference to the dialogue log storage unit 111 and stores the scenario in the scenario storage unit 110. The scenario update unit 107 updates the scenario object DB 114 with reference to the scenario storage unit 110. Specifically, the scenario update unit 107 converts the scenario stored in the scenario storage unit 110 into an object that can be executed by the dialogue control unit 103, and adds it to the scenario object DB 114 at an arbitrary timing. In one example, the scenario stored in the scenario storage unit 110 is a text-based scenario, and the scenario stored in the scenario object DB 114 is an object-based scenario. Note that the scenario stored in the scenario object DB 114 may be a text-based scenario.

  The scenario search unit 113 extracts a scenario feature word from the dialogue between the user and the operator, and selects a scenario associated with the scenario feature word from the scenario storage unit 110 as a similar scenario. The scenario feature word will be described later. The dialogue state display unit 112 displays a similar scenario. The dialogue state display unit 112 displays the analysis result of the dialogue between the user and the operator.

Next, the operation of the interactive system 100 will be described.
FIG. 2 schematically shows a procedure of dialog log recording of the dialog system 100. Here, the dialogue shown in FIG. 3 will be described as an example. In step S201 in FIG. 2, a dialogue between the user and the operator starts. At this time, the dialog extracting unit 105 records a dialog start label indicating the start of the dialog in the dialog log storage unit 111.

  In step S202, the user or operator speaks. In the dialog example of FIG. 3, the user first utters “Where do I receive the rental car booked last time?”. In step S203, the speech recognition unit 101 performs speech recognition on the utterance input in step S202. In the example of the dialog shown in FIG. 3, the text “Where do I receive the previously booked rental car?” Is obtained as the voice recognition result.

  In step S204, the intention understanding unit 102 understands the intention of the utterance from the voice recognition result, and outputs the intention understanding result. The intention understanding result includes an utterance type, an intention tag, and a semantic class. The type of utterance indicates the role of the utterance in the dialogue. As shown in FIG. 4, the types of utterances include “request”, “greeting”, “question”, “response”, “suggestion”, “confirmation”, “answer”, and the like. The utterance type is output in the form understandable by the machine, for example, as an utterance type ID. The intention tag is information indicating intentions such as “flight timetable display”, “car rental search”, “car rental location display”, “hotel fee search”, “hotel reservation”, etc. as shown in FIG. The intention tag is output in a form that can be understood by the machine, for example, as an intention tag ID.

  In step S205, the dialogue extraction unit 105 extracts any information of the intention tag, the attribute, the attribute value, and the action content from the utterance input in step S202, and the speech recognition result, the intention recognition result, and the extracted information. Are associated and recorded in the dialogue log storage unit 111. The process of step S205 will be described later.

  In step S206, it is determined whether or not the dialogue has ended. For example, when an utterance indicating the end of the dialog is detected or when the operator executes an action, it is determined that the dialog has ended. If the dialogue continues, the process returns to step S202. Returning to step S202, the next utterance occurs. In the dialogue example of FIG. 3, the operator speaks “Are you a rental car? Processing of steps S203, S204, and S205 is executed for this utterance. Similarly, the operator's utterance “Which is the airport?”, The user ’s utterance “XX airport”, the operator ’s utterance “Which airline are you using?”, The user ’s utterance “XX Air The operator's utterance “I will send you a map of where to pick up the rental car” is processed sequentially. The operator speaks “I will send you a map of the rental car reception location” and operates the computer terminal to send the map data to the user terminal. The dialogue extraction unit 105 detects the action of the operator based on the intention understanding result of the utterance “I will send you a map of the rental car reception location.” The dialogue extraction unit 105 acquires the content of the action executed during the response by the operator and records it in the dialogue log storage unit 111. As the actions, for example, as shown in FIG. 6, there are “car rental charge transfer”, “flight timetable display”, “airport facility information display”, “car rental search”, and the like. An action is associated with an action ID.

  When the dialogue ends, the process proceeds to step S207. In step S207, the dialog extracting unit 105 records a dialog end label indicating the end of the dialog in the dialog log storage unit 111, assuming that the dialog between the user and the operator has ended. In the dialog log storage unit 111, a log related to one dialog is recorded between a dialog start label and a dialog end label. The dialogue log related to one dialogue includes a dialogue analysis result, a scenario feature word, an intention tag, an attribute and its semantic class, an attribute value and its semantic class, and an action content.

The process of step S205 will be described in more detail.
In step S205-1, when the type of utterance input in step S202 is confirmation, the dialogue extraction unit 105 extracts a scenario feature word from this utterance and the utterance paired therewith. Specifically, the dialogue extraction unit 105 extracts a word common to one (for example, an operator) confirmation utterance and the other (for example, a user) utterance just before it as a scenario feature word. In the dialogue example of FIG. 3, the confirmation utterance is the operator's utterance “Is it a place to receive a rental car?”. The utterance paired with this utterance is the utterance of the user immediately before, “Where is the rental car reserved in advance? Common words are “rental car” and “receive”. Therefore, “rental car” and “receive” are extracted as scenario feature words.

  In step S205-2, the dialogue extraction unit 105 determines whether or not the type of utterance is a question. If the utterance type is a question, the process proceeds to step S205-3, and if not, the process proceeds to step S205-4. In step S205-4, the dialogue extraction unit 105 determines whether or not the type of utterance is an answer. If the utterance type is an answer, the process proceeds to step S205-5, and if not, the process proceeds to step S205-6. In step S205-6, the dialogue extraction unit 105 determines whether the utterance is related to the action of the operator. If the utterance is related to an action, the process proceeds to step S205-8; otherwise, the process proceeds to step S205-7.

  The dialogue extraction unit 105 acquires an attribute from the utterance of the question (step S205-3), and acquires an attribute value from the utterance of the answer paired with the utterance of the question (step S205-5). As shown in FIG. 7, the semantic class may be a hierarchical classification of meanings. The semantic class may not be expressed in a hierarchical structure. The attribute value is an argument for carrying out the intention indicated by the intention tag.

  Specifically, the dialogue extraction unit 105 acquires, as an attribute, a word that is uttering a question as an attribute from words having a common semantic class for the utterance of the question and the utterance of the answer. Get as a value. In the dialog example of FIG. 3, the user's answer to the operator's question “Which airport is?” Is “XX airport.”, And the semantic class common to these utterances is “Location_STATION_AIR”. In the operator's utterance “Which airport is?”, The word whose semantic class is “Location_STATION_AIR” is “airport”, and “airport” is extracted as an attribute. The word having the semantic class “Location_STATION_AIR” in the user's utterance “XX airport” is “XX airport”, and “XX airport” is extracted as an attribute value. Furthermore, the user's answer to the operator's question “Which airline are you using?” Is “XX Airline.” The semantic class common to these utterances is “Organization_COMPANEY_AIR”. In the operator's utterance “Which airline are you using?”, The word whose semantic class is “Organization_COMPANEY_AIR” is “airline”, and “airline” is extracted as an attribute. In the user's utterance “XX is aviation”, a word whose semantic class is “Organization_COMPANEY_AIR” is “XX aviation”, and “XX aviation” is extracted as an attribute value. From the dialogue example of FIG. 3, the combination of the attribute “airport”, attribute value “XX airport”, semantic class “Location_STATION_AIR”, attribute “airline”, attribute value “xx aviation”, semantic class “Organization_COMPANEY_AIR” A pair is obtained.

  The dialogue extraction unit 105 is not limited to the above example that extracts the same word appearing in the confirmation utterance and the utterance paired with this utterance as a scenario common word, but the operator's utterance such as a question and answer pair and the user The same word that appears in the pair of utterances may be extracted as a scenario common word.

  When the dialog extracting unit 105 detects the action of the operator, the dialog extracting unit 105 acquires the action content (step S205-8). The action content includes an operation actually performed on the system by the operator. FIG. 8 shows an example of action content obtained when the operator operates the application in relation to the dialogue example shown in FIG. The action content shown in FIG. 8 is to send a map showing a rental car receiving location.

  The dialogue extraction unit 105 acquires an intention tag from an utterance that is not any of the utterances related to the question, the answer, and the action (step 205-7). This utterance is recorded in the dialogue log storage unit 111 as an utterance having an intention not to contribute to the purpose of the dialogue.

  FIG. 9 shows a dialogue log related to the dialogue example shown in FIG. In FIG. 9, “START OPERATOR” is a dialog start label, and “END OPERATOR” is a dialog end label. Information about the utterance and action is recorded between the dialog start label and the dialog end label. In the example of FIG. 9, the utterance log is described as a utterance target: utterance type: utterance content: intention tag, separated by colons. The utterance content includes a speech recognition result, a word, and its semantic class. The semantic class is listed in parentheses immediately after the word. In addition, the action log is described in the form of action target: action content, separated by a colon.

  FIG. 10 schematically shows a processing procedure for constructing a scenario from the dialogue log. In step S301 of FIG. 10, the scenario construction unit 106 reads the dialogue log from the dialogue log storage unit 111, and extracts the dialogue start label and dialogue end label related to the dialogue that is the target of scenario construction from the read dialogue log. In step S302, the scenario construction unit 106 reads a log between the dialog start label and the dialog end label. In step S303, the scenario construction unit 106 generates “input”, “operation”, and “state” as the constituent units of the scenario. 11A and 11B show examples of scenarios constructed based on the dialogue log of FIG. The scenario shown in FIG. 11A includes three states. The scenario shown in FIG. 11B includes one state. Input includes intent tags and attributes. The action includes an action tag.

  In step S304, the scenario construction unit 106 acquires a semantic class common to an utterance whose type is a question and an utterance whose type is an answer and words of the semantic class. Here, “common” is used as a term having the meaning of “same” or “inclusive relationship”. The scenario construction unit 106 uses the acquired word (or semantic class) as an input attribute.

  The process of step S304 will be described in more detail. In step S304-1, the scenario construction unit 106 acquires a word as an attribute candidate from an utterance whose type is a question, and stores it in a memory. In step S304-2, when the next utterance type is an answer, the scenario construction unit 106 acquires a word from the utterance as an attribute candidate and stores it in the memory. In step S304-3, the semantic classes of the words acquired in steps S304-1 and S304-2 are compared, and words having a common semantic class are attributed. For example, an airport is acquired as an attribute from a pair of an operator's utterance “Which is an airport?” And a user's utterance “I am an airport”. Note that the attribute acquisition method may be the same as that described for the processing in step S205-3. From the dialogue log of FIG. 9, two attributes “airport” and “airline” are obtained.

  If the attribute is obtained in step S304-3, the process proceeds to step S304-5. In step S304-5, the scenario construction unit 106 generates an input condition using the attribute obtained in step S304-3. Specifically, the scenario construction unit 106 registers the attribute in the scenario as an input attribute corresponding to the intention tag of the latest utterance whose type is request.

  When the attribute is not obtained as in the case where the utterance next to the utterance of the question is not an answer, the process proceeds to step S304-4. In step S304-4, the scenario builder 106 determines whether or not the user has answered the question of the operator. For example, in the interactive example shown in FIG. 12, the user responds “Oh, I don't know” to the operator's question “Which terminal is?”. When the utterance type for the question is not an answer as described above, the scenario construction unit 106 determines that the response is a redundant response of the scenario (may be determined as another response type), that is, determines that the efficiency is low, and constructs Set the middle scenario rating low. In step S304-6, the scenario construction unit 106 waits for an utterance whose type is an answer. When the scenario construction unit 106 detects an utterance whose type is an answer, the scenario construction unit 106 acquires an attribute from the pair of the utterance of the question and the utterance of the answer, and generates an input condition based on the attribute.

  If the type of utterance next to the utterance of the question is not a question in step S304-4, the process proceeds to step S304-7. In S304-7, an intention tag is acquired by the intention understanding unit 102, and "input" is generated together with the input condition generated in S304-5.

  In step S305, the scenario construction unit 106 finishes reading the dialogue log. In step S306, the scenario construction unit 106 replaces a word included in the action content with a semantic class to make a variable. In step S307, the scenario construction unit 106 saves the constructed scenario in the scenario storage unit 110. The scenario is stored in association with the scenario feature word so that the scenario feature word can be searched.

  The scenario may be constructed so as to faithfully reproduce the dialogue between the user and the operator as in the example of FIG. 11A, and is constructed so as to accept necessary attributes at one time as in the example of FIG. 11B. May be.

  The scenario update unit 107 converts the scenario stored in the scenario storage unit 110 into an object that can be executed by the dialogue control unit 103, and adds the object to the scenario object DB 114. The update timing may be automatic or may be based on an operation by an administrator. Similar scenarios may be built simultaneously for multiple operators. As shown in FIG. 13, the scenario storage unit 110 stores a scenario in association with a scenario feature word, the number of states, the number of response steps, and the number of response failures. The number of response failures indicates the number of times the response has failed, such as when the user makes an utterance other than an answer to the operator's question. The number of states, the number of response steps, and the number of response failures are examples of evaluation data for evaluating a scenario used when the administrator of the interactive system 100 determines whether to add a scenario to the scenario object DB 111. is there. The scenario update unit 107 can display the evaluation data together with the scenario so that the administrator of the interactive system 100 can select the scenario to be added to the scenario object DB 114.

  FIG. 14 shows a procedure for presenting a candidate for an action to be executed to the responding operator. In step S401 in FIG. 14, the scenario search unit 113 extracts scenario feature words from the dialogue between the user and the operator during the operator's response. Specifically, the scenario search unit 113 extracts a word common to the utterance whose type is confirmation and the utterance paired therewith as a scenario feature word.

  In step S402, the scenario search unit 113 searches the scenario storage unit 110 using the scenario feature word as a search key. In step S403, it is determined whether there is a similar scenario that is a scenario in which all or some of the scenario feature words are matched. If there is a similar scenario, the process proceeds to step S404, and if not, the process ends.

In step S404, the scenario search unit 113 acquires action content included in the similar scenario. In step S405, the scenario search unit 113 displays the acquired action content as an action candidate through the dialog state display unit 112. The operator determines an action to be executed with reference to the displayed action candidates.
Displaying action candidates in this way can assist the operator.

  FIG. 15 shows an example of contents displayed by the dialog state display unit 112. The dialog state display unit 112 includes a conversation monitor, an intention understanding monitor, and an operation monitor. The conversation monitor displays a voice recognition result for the dialogue between the user and the operator by the voice recognition unit 101. The intention understanding monitor displays an intention understanding result for the dialogue between the user and the operator by the intention understanding unit 102. The operation monitor displays the action candidates acquired by the scenario search unit 113. In the example of FIG. 15, three action candidates are displayed.

  By providing the dialog state display unit 112, the operator can visually confirm the user's request. If the speech recognition result and the intention understanding result are incomplete, it is necessary to correct the speech recognition result and the intention understanding result in order to construct a useful scenario. In the example of FIG. 15, the intent understanding has failed because a misrecognition has occurred in the speech recognition. By presenting the voice recognition result and the intention understanding result to the operator during the response, the operator can correct the voice recognition result and the intention understanding result.

  As described above, according to the present embodiment, a necessary scenario can be easily added to the dialogue system by constructing a scenario based on the analysis result of the dialogue between the user and the operator and the dialogue log including the action of the operator. be able to.

  Note that the interactive system 100 of the embodiment can also be realized, for example, by using a general-purpose computer device as basic hardware. That is, the speech recognition unit 101, the intention understanding unit 102, the dialogue control unit 103, the response generation unit 104, the dialogue extraction unit 105, the scenario construction unit 106, the scenario update unit 107, the dialogue state display unit 112, and the scenario search unit 113 This can be realized by causing a processor mounted on the computer apparatus to execute the program. At this time, the interactive system may be realized by installing the above program in a computer device in advance, or may be stored in a storage medium such as a CD-ROM, or distributed through the network. The program may be implemented by appropriately installing it in a computer device. The dialogue log storage unit, scenario storage unit, dictionary storage unit, and intention storage unit are a memory, a hard disk or a CD-R, a CD-RW, a DVD-RAM, a DVD- It can be realized by appropriately using a storage medium such as R.

  Although several embodiments of the present invention have been described, these embodiments are presented by way of example and are not intended to limit the scope of the invention. These novel embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the scope of the invention. These embodiments and modifications thereof are included in the scope and gist of the invention, and are included in the invention described in the claims and the equivalents thereof.

DESCRIPTION OF SYMBOLS 100 ... Dialog system 101 ... Voice recognition part 102 ... Intent understanding part 103 ... Dialog control part 104 ... Response generation part 105 ... Dialog extraction part 106 ... Scenario construction part 107 ... Scenario update part 108 ... Dictionary Storage unit 109 ... Intent model storage unit 110 Scenario scenario storage unit 111 Dialog log storage unit 112 Dialog state display unit 113 Scenario search unit 114 Scenario object database

Claims (9)

A speech recognition unit that performs speech recognition on a plurality of utterances included in a dialogue between a user and an operator, and generates a speech recognition result including a plurality of texts corresponding to each of the plurality of utterances;
Understand each intention of each of the plurality of utterances based on each of the plurality of texts, and each type of the plurality of utterances, each intention of the plurality of utterances, a word included in the plurality of texts, An intent understanding unit that obtains an intent understanding result including a semantic class;
A dialogue information storage unit for storing the speech recognition result, the intention understanding result, and the action performed by the operator in association with the dialogue;
A scenario construction unit that obtains, as an attribute, a word having a common semantic class for the utterance of a question and the utterance of an answer included in the dialogue, and constructs a scenario using the attribute and the action;
A dialogue system construction support apparatus comprising:   The dialogue system construction support apparatus according to claim 1, further comprising a dialogue extraction unit that extracts, as scenario feature words, the same word that appears in a pair of the utterance of the operator and the utterance of the user included in the dialogue.   3. The dialogue system construction support apparatus according to claim 2, wherein the dialogue extraction unit extracts a common word between the confirmation utterance included in the dialogue and the utterance paired with the confirmation utterance as the scenario feature word. A scenario storage unit for storing the scenario in association with the scenario feature word;
A scenario search unit that searches the scenario storage unit and acquires a scenario associated with the scenario feature word extracted by the dialog extraction unit as a similar scenario;
The dialogue system construction support apparatus according to claim 2, further comprising a display unit that displays an action included in the similar scenario.   The dialogue system construction support apparatus according to claim 1, further comprising a display unit that displays the voice recognition result and the intention recognition result.   The dialogue system construction support apparatus according to claim 1, further comprising a scenario update unit that adds the scenario to a database of the dialogue system. The scenario construction unit generates evaluation data for evaluating the scenario,
The dialogue system construction support apparatus according to claim 6, wherein the scenario update unit displays the scenario together with the evaluation data so that it can be selected whether or not to add the scenario to the database. Performing speech recognition on a plurality of utterances included in a dialog between a user and an operator, and generating a speech recognition result including a plurality of texts corresponding to each of the plurality of utterances;
Understand each intention of each of the plurality of utterances based on each of the plurality of texts, and each type of the plurality of utterances, each intention of the plurality of utterances, a word included in the plurality of texts, Obtaining intent understanding results including semantic classes;
Storing the speech recognition result, the intention understanding result, and the action performed by the operator in relation to the dialogue in association with each other;
Obtaining a word having a common semantic class for the utterance of the question and the utterance of the answer included in the dialogue as an attribute, and constructing a scenario using the attribute and the action;
A dialogue system construction support method comprising: Computer
Speech recognition means for performing speech recognition on a plurality of utterances included in a dialogue between a user and an operator, and generating a speech recognition result including a plurality of texts corresponding to each of the plurality of utterances;
Understand each intention of each of the plurality of utterances based on each of the plurality of texts, and each type of the plurality of utterances, each intention of the plurality of utterances, a word included in the plurality of texts, An intent understanding means for obtaining an intent understanding result including a semantic class;
Storage means for associating and storing the speech recognition result, the intention understanding result, and an action performed by the operator in relation to the dialogue;
Constructing a dialogue system for acquiring words having a common semantic class for the utterance of the question and the utterance of the answer included in the dialogue as attributes and functioning as scenario construction means for constructing a scenario using the attributes and the actions Support program.

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