【０００１】[0001]
【発明の属する技術分野】この発明は、利用者の自然言
語入力を理解して情報提供サービスの自動応答を行なう
音声対話システムに関するものである。[0001] 1. Field of the Invention [0002] The present invention relates to a speech dialogue system for understanding a user's natural language input and automatically responding to an information providing service.
【０００２】[0002]
【従来の技術】情報システムにおけるマンマシンインタ
フェース技術として、従来から、利用者と自然言語によ
る対話を行なって自動応答システムを実現する対話技術
があり、特に、利用者と音声による対話を行なって実現
する音声対話技術への要求が高まっている。音声対話技
術の応用システムとして、例えば、受付、注文、予約な
どの各種サービス代行や、利用者が要求する情報の提供
を行なう電話音声自動応答装置が知られており、２４時
間サービス化、業務の効率化、省力化などの点で有用性
が高い。2. Description of the Related Art As a man-machine interface technology in an information system, there has been a conventional technology for realizing an automatic response system by performing a dialogue with a user in a natural language. There is an increasing demand for spoken dialogue technology. As an application system of the voice interaction technology, for example, a telephone voice automatic response device for providing various services such as reception, order, reservation, and providing information requested by a user is known. It is highly useful in terms of efficiency and labor saving.
【０００３】このような電話系サービスの分野では、Ｃ
ＴＩ（Ｃｏｍｐｕｔｅｒ Ｔｅｌｅｐｈｏｎｙ Ｉｎｔ
ｅｇｒａｔｉｏｎ）システムの導入が最近急速に進んで
いる。この分野では、顧客の満足度を向上させるため
に、発信呼通知によって顧客を特定し、過去の顧客情報
を利用して、顧客個人にあった情報提供や応対のサービ
スが試みられている。特に、音声自動応答装置を用いて
業務の自動化を図るＣＴＩシステムでは、人間のオペレ
ータ代行に伴うサービスの質の低下に対し、いかにして
顧客の満足度を向上させるかが大きな課題となってお
り、顧客個人に適応した応対を実現する音声対話技術が
必要となる。In the field of such telephone services, C
TI (Computer Telephony Int)
In recent years, the introduction of an egg system has been rapidly progressing. In this field, in order to improve customer satisfaction, an attempt is made to provide a customer with a personalized information service by using a past customer information by specifying a customer by an outgoing call notification. In particular, in a CTI system that automates business using an automatic voice response device, how to improve customer satisfaction has become a major issue with respect to a decrease in service quality due to human operator agency. In addition, a speech dialogue technology that realizes a response adapted to an individual customer is required.
【０００４】音声対話技術により構築される音声対話シ
ステムでは、一般的な構成として、利用者の発話を認識
する音声認識部、認識された発話文をシステムへのコマ
ンドへ翻訳する音声理解部、コマンドで表現された利用
者の要求に応じて、データベース検索や予約などを行な
うアプリケーションを制御し、利用者とシステムとの対
話を管理して、システムの応答を決定する対話管理部、
システムの応答を音声で通知する音声合成部を備えてい
る。[0004] In a speech dialogue system constructed by a speech dialogue technology, a speech recognition unit for recognizing a user's utterance, a speech understanding unit for translating a recognized speech sentence into a command for the system, and a command as a general configuration. A dialog management unit that controls an application that performs a database search, a reservation, and the like in accordance with a user's request expressed in, manages a dialog between the user and the system, and determines a response of the system.
A voice synthesizer for notifying the response of the system by voice is provided.
【０００５】個人性を考慮した応対を実現する音声対話
技術としては、従来から、音声合成部からのシステムの
応答に対する利用者の入力のタイミングにより、システ
ムに対する利用者の習熟度を推定し、音声ガイダンスの
内容を習熟度に合わせて変更する技術（特開平４−３４
４９３０号）、利用者の発話に対する音声認識部での音
響尤度と、対話管理部による認識結果の確認対話で判明
する認識失敗回数とを用いて、利用者の音声が認識しや
すいか否かを推定し、認識のしやすさに応じて確認対話
の制御方法を変更する技術（特開平７−１８１９９４
号）、発信呼の電話番号により利用者を特定した後に、
利用者の年齢（大人、子供）や国籍（言語）に合わせ
て、ガイダンスの文体や言語を変更する技術（特開平８
−１１６５７２号）などがある。[0005] As a speech dialogue technology for realizing a response in consideration of personality, conventionally, a user's proficiency in a system is estimated based on a timing of a user's input to a system response from a speech synthesis unit, and a speech is spoken. Technology for changing the contents of guidance according to the level of proficiency (Japanese Patent Laid-Open No. 4-34)
No. 4930), whether or not the user's voice is easy to recognize using the acoustic likelihood of the user's utterance in the voice recognition unit and the number of recognition failures found in the confirmation dialogue of the recognition result by the dialog management unit (Japanese Patent Laid-Open No. Hei 7-181994) in which the control method of the confirmation dialog is changed according to the ease of recognition.
Number), and after identifying the user by the phone number of the outgoing call,
Technology for changing the style and language of guidance according to the age (adult, child) and nationality (language) of the user
-116572).
【０００６】[0006]
【発明が解決しようとする課題】しかし、上記のような
音声対話システムでは、利用者の発話文をシステムへの
コマンドへ翻訳する音声理解技術において、個人性が考
慮された翻訳がなされてなく、利用者から入力された発
話文の翻訳結果は、全ての利用者に関して差異のない翻
訳結果となっていた。However, in the above-described speech dialogue system, in a speech understanding technology for translating a user's utterance sentence into a command to the system, translation in consideration of personality is not performed. The translation result of the utterance sentence input by the user was a translation result having no difference for all users.
【０００７】例えば、ホテルの検索のような情報検索型
のサービスにおける対話では、利用者が希望条件に合う
ホテルを探すときに、「横浜で安いホテルを教えて下さ
い」といった、漠然と料金の希望を指定する発話が頻繁
に生じる。このような「安い」という曖昧な単語に対し
ては、一般的に、設計者が予め想定した固定の値、例え
ば６０００円以下という値を一律に用いてコマンドへ翻
訳する。[0007] For example, in a dialogue in an information search type service such as a hotel search, when a user searches for a hotel that meets desired conditions, he / she may vaguely request a price such as "Please tell me a cheap hotel in Yokohama." The specified utterance occurs frequently. Such an ambiguous word "cheap" is generally translated into a command using a fixed value assumed by the designer in advance, for example, a value of 6000 yen or less.
【０００８】このために、１００００円程度が安くて手
頃だと思って探している利用者に対して、システムは
「横浜の安いホテルは、Ａホテル４５００円、Ｂホテル
５５００円、Ｃホテル６０００円、があります」のよう
な応答を行ない、利用者は再度、「もう少し高めのホテ
ルが良いのですが」といった発話が必要になるため、検
索が効率的でないという課題があった。また、利用者の
料金に対する感覚に一致していないために、利用者に違
和感を生じさせるという課題があった。[0008] For this reason, for users who are looking for a cheap and affordable price of about 10000 yen, the system provides the following: "A cheap hotel in Yokohama is A hotel 4500 yen, B hotel 5500 yen, C hotel 6000 yen. There is a problem that the search is not efficient because the user needs to make an utterance such as "I'd like a slightly higher hotel" again. In addition, there is a problem that the user does not feel comfortable because the user does not agree with the fee.
【０００９】この発明は、上記課題を解決するためにな
されたもので、利用者の曖昧語を含む自然言語の入力に
対して、効率的な検索ができる音声対話システムを提供
することを目的とする。また、この発明は、利用者から
入力される自然言語に含まれている曖昧語に対応する意
味を推定して、効率的かつ柔軟な検索ができる音声対話
システムを提供することを目的とする。また、この発明
は、利用者が対話システムを利用した回数が少ない場合
でも、利用者の感覚に合致した自然な情報提示を行なう
ことができ、情報検索の効率化、及び利用者の利便性を
向上させることができる音声対話システムを提供するこ
とを目的とする。また、この発明は、曖昧な語が表わす
値を利用者の発話履歴から学習して、利用者に応じて自
動的に設定して翻訳できるようにし、情報検索の効率
化、及び利用者の感覚に合致した自然な情報提示を行な
うことで、利用者の利便性を向上させる音声対話システ
ムを提供することを目的とする。SUMMARY OF THE INVENTION The present invention has been made to solve the above problems, and has as its object to provide a speech dialogue system capable of performing an efficient search for a user's input of a natural language including an ambiguous word. I do. Another object of the present invention is to provide a speech dialogue system that can estimate a meaning corresponding to an ambiguous word included in a natural language input by a user and perform an efficient and flexible search. In addition, the present invention can provide natural information that matches the user's sense even when the user has used the dialogue system a small number of times, thereby improving the efficiency of information retrieval and the convenience of the user. It is an object of the present invention to provide a speech dialogue system that can be improved. Further, the present invention learns the value represented by an ambiguous word from a user's utterance history, automatically sets and translates the value according to the user, thereby improving the efficiency of information retrieval and the user's sense. It is an object of the present invention to provide a voice interaction system that improves user convenience by performing natural information presentation that conforms to.
【００１０】[0010]
【課題を解決するための手段】この発明に係る音声対話
システムは、対話システム動作に対応して定義されたコ
マンド意図、対話システム動作のパラメータの種類を定
義した項目、及び項目に対応する値である項目値からな
る表現を対話システムのコマンドとし、自然言語をコマ
ンドへ変換するための変換知識をコマンド知識として記
憶するコマンド知識記憶手段と、自然言語において項目
値へ一意に変換できない語を曖昧語とし、曖昧語、曖昧
語の項目、及び曖昧語に対応する意味標識を曖昧語辞書
として記憶する曖昧語辞書記憶手段と、曖昧語辞書記憶
手段に記憶された曖昧語辞書を参照して、利用者が入力
した自然言語に含まれる曖昧語を曖昧語に対応する意味
標識に置換して、曖昧語の項目と意味標識の対を作成
し、コマンド知識記憶手段に記憶されたコマンド知識を
参照して、入力された自然言語を、曖昧語の項目と意味
標識の対を含んだコマンドに変換するコマンド変換手段
と、曖昧語に対応する意味標識の値を推定するための推
定値情報を利用者を特定する利用者識別子とともに記憶
する推定値情報記憶手段と、コマンド変換手段から入力
される曖昧語の項目と意味標識の対を含んだコマンドに
対し、推定値情報記憶手段に記憶された利用者識別子に
対応した推定値情報を参照して、曖昧語に対応する意味
標識の推定値を決定してコマンドとともに出力する曖昧
語翻訳手段とを備えたものである。SUMMARY OF THE INVENTION A voice dialogue system according to the present invention includes a command intention defined corresponding to a dialogue system operation, an item defining a type of a parameter of the dialogue system operation, and a value corresponding to the item. A command knowledge storage means for storing an expression consisting of a certain item value as a command of a dialog system and storing conversion knowledge for converting a natural language into a command as command knowledge, and an ambiguous word for a word which cannot be uniquely converted to an item value in a natural language An ambiguous word dictionary storing means for storing an ambiguous word, an ambiguous word item, and a meaning indicator corresponding to the ambiguous word as an ambiguous word dictionary, and referring to the ambiguous word dictionary stored in the ambiguous word dictionary storing means. The ambiguous words included in the natural language input by the user are replaced with semantic indicators corresponding to the ambiguous words, and pairs of ambiguous word items and semantic indicators are created, and command knowledge notes are created. Command conversion means for converting the input natural language into a command including a pair of an ambiguous word item and a semantic indicator with reference to the command knowledge stored in the means, and a value of the semantic indicator corresponding to the ambiguous word. Estimation value information storage means for storing estimation value information for estimation together with a user identifier for identifying a user, and estimation for a command containing a pair of an ambiguous word item and a meaning indicator input from the command conversion means. Referring to the estimated value information corresponding to the user identifier stored in the value information storage means, determining an estimated value of the meaning indicator corresponding to the ambiguous word, and outputting the command along with the ambiguous word translating means. is there.
【００１１】この発明に係る音声対話システムにおい
て、曖昧語の意味標識と、該意味標識に対応する推定値
との関係を関数として規定し、補間モデルとして記憶し
た補間モデル記憶手段と、曖昧語翻訳手段からの利用者
識別子及び曖昧語の意味標識を入力とし、利用者識別子
に対応した推定値情報における曖昧語のうち、入力され
た意味標識の推定値情報が未学習である曖昧語に対し
て、補間モデル記憶手段の補間モデルを用いて、学習済
の曖昧語の意味標識に対する推定値情報から、未学習の
意味標識の推定値を算出して曖昧語翻訳手段へ出力する
推定値補間手段とを備えたものである。In the speech dialogue system according to the present invention, an interpolation model storage means for defining a relation between a meaning marker of an ambiguous word and an estimated value corresponding to the meaning marker as a function and storing the function as an interpolation model, and an ambiguous word translation The user identifier and ambiguous word semantic sign from the means are input, and among the ambiguous words in the estimated value information corresponding to the user identifier, the ambiguous word for which the input estimated sign information of the meaning sign is unlearned An estimated value interpolating means for calculating an estimated value of an unlearned semantic sign from the estimated value information for the semantic sign of the learned vague word using the interpolation model of the interpolated model storing means and outputting the estimated value to the ambiguous word translating means; It is provided with.
【００１２】この発明に係る音声対話システムにおい
て、全ての利用者に対する推定値情報を記憶する全利用
者推定値情報記憶手段と、曖昧語翻訳手段からの利用者
識別子及び曖昧語の意味標識を入力とし、利用者識別子
に対応した推定値情報における曖昧語のうち、入力され
た意味標識の推定値情報が未学習である曖昧語に対し
て、全利用者推定値情報記憶手段に記憶された全ての利
用者に対する推定値情報を参照して、学習済の曖昧語の
意味標識に対する推定値情報との一致度が高い他の利用
者の推定値情報を利用し、未学習の意味標識の推定値を
選択して曖昧語翻訳手段へ出力する推定値選択手段とを
備えたものである。In the voice dialogue system according to the present invention, all user estimated value information storage means for storing estimated value information for all users, and user identifiers and ambiguous word meaning indicators from ambiguous word translation means are input. Of the ambiguous words in the estimated value information corresponding to the user identifier, all of the ambiguous words for which the input estimated value information of the semantic sign is unlearned are stored in the all user estimated value information storage means. Estimated value of unlearned semantic sign using the estimated value information of other users that has a high degree of matching with the estimated value information of the semantic sign of the learned ambiguous word by referring to the estimated value information for the user of And an estimated value selecting means for selecting and outputting to the ambiguous word translating means.
【００１３】この発明に係る音声対話システムにおい
て、項目及び項目値が付与された検索対象データの集合
を記憶するデータベースと、入力されたコマンドに対応
して、所定の対話システム動作を実行してシステムと利
用者との対話を管理するとともにデータベースを検索
し、利用者へ通知する応答文の意味内容を表わす応答意
味表現を生成する対話管理手段とを備えたものである。In the voice dialogue system according to the present invention, a database for storing a set of search target data to which items and item values are assigned, and a system for executing a predetermined dialogue system operation in response to an input command And a dialog management means for managing a dialog between the user and the user, searching the database, and generating a response meaning expression representing the meaning of the response sentence to be notified to the user.
【００１４】この発明に係る音声対話システムにおい
て、対話管理手段で生成された応答意味表現を、対話の
開始からの応答順に記憶する応答履歴記憶手段と、推定
値の学習対象となる曖昧語の意味標識を、曖昧語の項目
とともに、対話の開始からの入力順に記憶する曖昧語記
憶手段と、曖昧語の意味標識の推定値を、応答履歴記憶
手段に記憶された応答意味表現と、コマンド変換手段か
ら入力されたコマンドとの関係から判定するための知識
を推定知識として記憶する推定知識記憶手段と、コマン
ド変換手段から入力されたコマンドに曖昧語の意味標識
が含まれる場合に曖昧語記憶手段へ意味標識を登録し、
推定知識記憶手段の推定知識を用いて、入力されたコマ
ンド及び応答履歴記憶手段の応答から、登録された曖昧
語の意味標識に対する推定値を推定し、利用者識別子に
対応した推定値情報記憶手段の推定値情報を更新して学
習し、学習の対象とした曖昧語の意味標識を曖昧語記憶
手段から削除する推定値適応手段とを備えたものであ
る。In the speech dialogue system according to the present invention, response history storage means for storing the response meaning expressions generated by the dialogue management means in the order of responses from the start of the dialogue, and the meaning of the ambiguous word for which the estimated value is to be learned An ambiguous word storage means for storing the sign together with the ambiguous word item in the order of input from the start of the dialogue; a response meaning expression stored in the response history storage means for the estimated value of the meaning sign of the ambiguous word; Estimated knowledge storage means for storing knowledge for judging from the relationship with the command input from the CPU as estimated knowledge, and to the fuzzy word storage means when the command input from the command conversion means includes an ambiguous word meaning indicator Register a semantic sign,
Using the estimated knowledge of the estimated knowledge storage means, an estimated value for the registered meaning marker of the ambiguous word is estimated from the input command and the response of the response history storage means, and the estimated value information storage means corresponding to the user identifier And an estimated value adapting means for learning by updating the estimated value information of the ambiguous word and deleting a meaning marker of the ambiguous word targeted for learning from the ambiguous word storage means.
【００１５】[0015]
【発明の実施の形態】以下、この発明の実施の一形態を
説明する。 実施の形態１．図１は、この発明の実施の形態１におけ
る音声対話システムの機能ブロック構成図であり、図に
おいて、１はコマンド知識記憶部（コマンド知識記憶手
段）、２はコマンド変換部（コマンド変換手段）、３は
データベース、４は応答履歴記憶部（応答履歴記憶手
段）、５は対話管理部（対話管理手段）、６は曖昧語辞
書記憶部（曖昧語辞書記憶手段）、７は推定値情報記憶
部（推定値情報記憶手段）、８は曖昧語翻訳部（曖昧語
翻訳手段）、９は曖昧語記憶部（曖昧語記憶手段）、１
０は推定知識記憶部（推定知識記憶手段）、１１は推定
値適応部（推定値適応手段）である。DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS One embodiment of the present invention will be described below. Embodiment 1 FIG. FIG. 1 is a functional block diagram of a voice dialogue system according to Embodiment 1 of the present invention. In FIG. 1, 1 is a command knowledge storage unit (command knowledge storage unit), 2 is a command conversion unit (command conversion unit), Reference numeral 3 denotes a database, 4 denotes a response history storage unit (response history storage unit), 5 denotes a dialogue management unit (dialogue management unit), 6 denotes an ambiguous word dictionary storage unit (ambiguous word dictionary storage unit), and 7 denotes an estimated value information storage unit. (Estimated value information storage means), 8 is an ambiguous word translation section (ambiguous word translation means), 9 is an ambiguous word storage section (ambiguous word storage means), 1
0 is an estimated knowledge storage unit (estimated knowledge storage unit), and 11 is an estimated value adaptation unit (estimated value adaptation unit).
【００１６】次に動作について説明する。まず、利用者
からの自然言語がコマンド変換部２へ入力される。入力
される自然言語は、利用者の発話を音声認識した結果の
テキストである。ただし入力可能なものとしては利用者
からの自然言語に限定するものではない。キーボードや
ＧＵＩなどの別の手段から入力されたテキストであって
も構わない。さらに、入力された自然言語に対し、コマ
ンド変換の前段階として、形態素解析や構文解析、意味
解析などの言語処理が施された結果の、意味的な構造を
持った表現形式である意味表現であってもよい。Next, the operation will be described. First, a natural language from a user is input to the command conversion unit 2. The input natural language is a text resulting from speech recognition of the utterance of the user. However, what can be input is not limited to the natural language from the user. The text may be input from another means such as a keyboard or a GUI. Furthermore, as a pre-stage of command conversion, the input natural language is subjected to linguistic processing such as morphological analysis, syntactic analysis, and semantic analysis, resulting in a semantic expression that has a semantic structure. There may be.
【００１７】次に、コマンド変換部２は、コマンド知識
記憶部１に記憶されたコマンド知識に従って、入力され
た自然言語を対話システムへのコマンドに変換する。コ
マンド知識記憶部１には、自然言語とコマンドとの対応
を記述したコマンド知識が記憶されている。コマンドの
定義の一例としては、コマンド＝意図：（項目１、項目
値１）、（項目２、項目値２）、…、（項目ｎ、項目値
ｎ）、のように表現し、コマンドを、意図と、そのパラ
メータとなる項目及び項目値の対の組み合わせで表現す
る。ここで、意図は対話システムの動作に対応して定義
し、項目は検索対象データに関する検索条件の種類に対
応して定義する。項目値は項目に属する具体的な値であ
る。例えば、ホテル予約の場合、意図としては、＜意
図：検索要求＞、＜意図：予約要求＞、＜意図：項目質
問＞、＜意図：項目値確認＞、＜意図：項目値表明＞、
＜意図：肯定＞、＜意図：否定＞、などであり、項目及
び項目値の対としては、（＜場所＞、横浜）、（＜料金
＞、６０００≧）、（＜部屋タイプ＞、シングル）、
（＜人数＞、２）、（＜対象＞、ホテル）、などであ
る。Next, the command conversion unit 2 converts the input natural language into a command for the interactive system according to the command knowledge stored in the command knowledge storage unit 1. The command knowledge storage unit 1 stores command knowledge describing the correspondence between a natural language and a command. As an example of the definition of the command, the command is expressed as follows: command = intention: (item 1, item value 1), (item 2, item value 2), ..., (item n, item value n). It is expressed by a combination of an intention and a pair of an item and an item value that are parameters. Here, the intention is defined corresponding to the operation of the interactive system, and the item is defined corresponding to the type of the search condition regarding the search target data. The item value is a specific value belonging to the item. For example, in the case of a hotel reservation, the intentions are <intention: search request>, <intention: reservation request>, <intention: item question>, <intention: item value confirmation>, <intention: item value expression>,
<Intention: affirmation>, <intention: negation>, and the like, and pairs of item and item value are (<place>, Yokohama), (<charge>, 6000 ≧), (<room type>, single) ,
(<Number of people>, 2), (<object>, hotel), and the like.
【００１８】コマンド知識記憶部１に記憶されているコ
マンド知識は、上記のコマンド表現と、自然言語との対
応関係を規定するための知識である。例えば、「教えて
下さい」、「ありますか」、「探しているのですが」、
などの自然言語に対しては、＜意図：検索要求＞が対応
し、「どこですか」、「いくらですか」、に対しては、
＜意図：項目質問＞が対応する。また、例えば、「横浜
で」に対しては、項目及び項目値の対として、（＜場所
＞、横浜）が対応し、「６０００円以下の」に対して
は、（＜料金＞、６０００≧）が対応する。コマンド知
識は、これらの対応関係について、自然言語に関する形
態素情報や助詞、助動詞などの意味的な情報を用いて、
対応表や変換規則などの形式で表現する。The command knowledge stored in the command knowledge storage unit 1 is knowledge for defining the correspondence between the above-mentioned command expression and a natural language. For example, "Tell me", "Are you there", "I'm looking for",
<Intention: search request> corresponds to natural language such as, and "where" and "how much"
<Intention: Item question> corresponds. Also, for example, (<Yokohama>) corresponds to (<place>, Yokohama) as a pair of an item and an item value, and (<fee>, 6000 ≧ ) Corresponds. Command knowledge uses semantic information such as morphological information about natural language, particles, auxiliary verbs, etc.
Expressed in a format such as a correspondence table or conversion rule.
【００１９】さらに、コマンド変換部２は、「安い」、
「近い」などのような項目値が一意に決定できない曖昧
語に対して、曖昧語辞書記憶部６に記憶された、曖昧語
と、曖昧語の項目と、曖昧語に対応する意味標識の対応
関係を参照し、入力に含まれる曖昧語を、曖昧語に対応
する意味標識に置換して、曖昧語の項目と意味標識の対
を作成する。さらに、コマンド知識を参照して、入力さ
れた自然言語を、上記曖昧語の項目と意味標識の対を含
んだコマンドの表現に変換する。Further, the command conversion unit 2 is provided with "cheap",
For ambiguous words such as “close” for which the item value cannot be uniquely determined, correspondence between ambiguous words, ambiguous word items, and meaning markers corresponding to the ambiguous words stored in the ambiguous word dictionary storage unit 6 By referring to the relationship, the ambiguous word included in the input is replaced with a meaning indicator corresponding to the ambiguous word, and a pair of the ambiguous word item and the meaning indicator is created. Further, referring to the command knowledge, the input natural language is converted into a command expression including a pair of the ambiguous word item and the meaning indicator.
【００２０】図２に曖昧語辞書記憶部６に記憶する対応
関係の例を示す。例えば、項目＜料金＞に関しては、曖
昧語「自立語（安い）」に対して意味標識「＄ｃｈｅａ
ｐ１」が対応している。コマンド変換部２は、入力され
た自然言語に曖昧語「安い」が含まれていれば、上記の
対応関係を参照して、（＜料金＞、＄ｃｈｅａｐ１）に
変換する。以上より、例えば、「横浜で安いホテルを教
えて下さい」という自然言語は、コマンド変換部２によ
り、「＜意図：検索要求＞：（＜場所＞、横浜）、（＜
料金＞、＄ｃｈｅａｐ１）、（＜対象＞、ホテル）」と
いうコマンドに変換される。FIG. 2 shows an example of the correspondence relationship stored in the ambiguous word dictionary storage unit 6. For example, regarding the item <charge>, the meaning marker “@chea” is used for the ambiguous word “independent word (cheap)”.
p1 "corresponds. If the input natural language includes an ambiguous word “cheap”, the command conversion unit 2 refers to the above correspondence and converts it into (<charge>, $ cheap1). From the above, for example, the natural language “Tell me a cheap hotel in Yokohama” is converted by the command conversion unit 2 into “<intention: search request>: (<place>, Yokohama), (<
Charge>, {cheap1), (<target>, hotel) ".
【００２１】曖昧語翻訳部８は、コマンド変換部２から
入力されたコマンド中に曖昧語の意味標識が含まれてい
る場合には、推定値情報記憶部７で記憶されている利用
者毎の推定値情報から、現在システムを対話している利
用者の利用者識別子に対応する推定値情報を参照し、曖
昧語の推定値を決定してコマンド中の曖昧語の意味標識
を決定された推定値に置き換え、対話管理部５へ出力す
る。When the command input from the command conversion unit 2 includes a meaning indicator of the vague word, the fuzzy word translating unit 8 stores the estimated value information storage unit 7 for each user. From the estimated value information, reference is made to the estimated value information corresponding to the user identifier of the user who is currently interacting with the system, the estimated value of the ambiguous word is determined, and the meaning indicator of the ambiguous word in the command is determined. The value is replaced with a value and output to the dialog management unit 5.
【００２２】推定値情報記憶部７は、曖昧語と曖昧語に
対応する意味標識の推定値情報を利用者毎に記憶する。
推定値情報は、利用者が過去の対話で曖昧語をどんな値
として用いたかの情報を記録したものであり、利用者と
システムとの対話の履歴を利用して、後述する推定値適
応部１１により学習される。なお、利用者が初めてシス
テムと対話する場合には、曖昧語の意味標識に対して初
期に設定された値が推定値情報として用いられる。The estimated value information storage unit 7 stores, for each user, estimated value information of ambiguous words and meaning markers corresponding to the ambiguous words.
The estimated value information is a record of information as to what value the user used an ambiguous word in a past dialogue. The estimated value information is used by an estimated value adapting unit 11 described later using a history of the dialogue between the user and the system. Learned. When the user interacts with the system for the first time, the value initially set for the meaning marker of the ambiguous word is used as the estimated value information.
【００２３】対話管理部５は、コマンドが入力される
と、設定された所定の対話手順に基づいて、コマンドに
対応したシステムの動作を実行し、システムと利用者と
の対話を管理する。所定の対話手順の一例としては、例
えば、コマンドの意図が検索要求であれば、対話管理部
５は、コマンドのパラメータである項目及び項目値の対
を用いて検索式を作成してデータベース３の検索を行な
い、検索結果を利用者へ通知するための応答の意味表現
を出力する。データベース３は、項目及び項目値が付与
された検索対象データの集合を記憶する。図３はデータ
ベース３に記憶される検索対象データの例であり、各対
象名に対し、項目と項目値のデータが与えられている。When a command is input, the dialog management unit 5 executes an operation of the system corresponding to the command based on a set predetermined dialog procedure, and manages a dialog between the system and a user. As an example of the predetermined dialogue procedure, for example, if the intention of the command is a search request, the dialogue management unit 5 creates a search formula using pairs of items and item values, which are parameters of the command, and creates a search expression. Performs a search and outputs a semantic expression of the response for notifying the user of the search result. The database 3 stores a set of search target data to which items and item values are assigned. FIG. 3 shows an example of search target data stored in the database 3, in which data of an item and an item value are given to each object name.
【００２４】あるいは、所定の対話手順についての他の
例としては、コマンドの意図が予約要求である場合、予
約に必須の項目、例えば、＜対象名＞、＜予約日＞、＜
人数＞、＜部屋タイプ＞、などに対する項目値が全て得
られていれば、予約動作の確認を利用者に行なって、確
認後に予約動作の実行を行ない、全て得られていない場
合には、不足している項目の項目値を利用者に質問する
ための応答の意味表現を出力する。Alternatively, as another example of the predetermined interactive procedure, when the intention of the command is a reservation request, items required for reservation, for example, <target name>, <reservation date>, <
If all of the item values for <number of people>, <room type>, etc. have been obtained, the reservation operation is confirmed to the user, and the reservation operation is performed after the confirmation. Outputs the semantic expression of the response for asking the user for the item value of the item being asked.
【００２５】応答の意味表現は、システムが利用者へ通
知する応答文を生成するための表現形式である。一般的
な音声自動応答装置では、応答の意味表現から応答文を
生成する文生成手段と、文生成手段から受け取った応答
文を合成音声へ変換する音声合成手段とを備えており、
対話管理部５から出力される応答の意味表現は音声とし
て利用者に通知される。The semantic expression of the response is an expression format for generating a response sentence that the system notifies the user. A general automatic voice response apparatus includes a sentence generation unit that generates a response sentence from a semantic expression of a response, and a voice synthesis unit that converts a response sentence received from the sentence generation unit into synthesized speech.
The meaning expression of the response output from the dialog management unit 5 is notified to the user as voice.
【００２６】例えば、この応答の意味表現としては、利
用者の「横浜駅で６０００円以下のホテルを教えて下さ
い」という入力に対してシステムがデータベース検索を
行なった結果が、Ａホテル４５００円、Ｂホテル５５０
０円、Ｃホテル６０００円、の３件である場合、その応
答の意味表現は、「＜検索結果提示＞：（対象名 Ａホ
テル（＜料金＞ ４５００円））、（対象名 Ｂホテル
（＜料金＞ ５５００円））、（対象名 Ｃホテル（＜料
金＞ ６０００円））」のような形式となる。For example, as a semantic expression of this response, the result of a database search performed by the system in response to the user's input “Please tell me the hotel at Yokohama Station that is less than 6000 yen” is A hotel 4500 yen, B Hotel 550
In the case of three cases of 0 yen and C hotel 6000 yen, the semantic expression of the response is “<search result presentation>: (target name A hotel (<rate> 4500 yen)), (target name B hotel (<Price> 5500 yen)), (target name C Hotel (<rate> 6000 yen)).
【００２７】さらに、対話管理部５は、利用者が対話を
開始してからの応答の意味表現を、対話の開始から応答
順に付与される応答識別番号とともに応答履歴記憶部４
に記録する。以上が、推定値情報記憶部７に記憶された
利用者個人に対応した推定値情報を利用して、曖昧語の
推定値を決定する場合の動作例である。Further, the dialog management unit 5 stores the semantic expression of the response after the user starts the dialog together with the response identification numbers assigned in the order of response from the start of the dialog and the response history storage unit 4.
To record. The above is the operation example in the case where the estimated value of the vague word is determined by using the estimated value information corresponding to the individual user stored in the estimated value information storage unit 7.
【００２８】次に、推定値情報記憶部７に記憶される推
定値情報を学習する場合の動作例について説明する。曖
昧語記憶部９は、曖昧語の意味標識を曖昧語の項目とと
もに記憶するものであり、対話の開始時からの入力識別
番号が付与された形式で記憶する。例えば、対話の３番
目の発話で入力されたコマンドが、「＜意図：検索要求
＞：（＜場所＞、横浜）、（＜料金＞、＄ｃｈｅａｐ
１）、（＜対象＞、ホテル）」の場合、（３：＜料金
＞、＄ｃｈｅａｐ１）という形式のデータが、曖昧語記
憶部９に登録される。推定値適応部１１は、コマンド変
換部２から入力されたコマンドに曖昧語の意味標識が含
まれる場合に、まず、曖昧語記憶部９へ曖昧語の意味標
識を上記の形式で登録する。Next, an example of the operation when learning the estimated value information stored in the estimated value information storage unit 7 will be described. The ambiguous word storage unit 9 stores the meaning indicator of the ambiguous word together with the item of the ambiguous word, and stores it in a form to which an input identification number from the start of the dialog is added. For example, the command input in the third utterance of the dialogue is “<intention: search request>: (<place>, Yokohama), (<fee>, @cheap
1), (<target>, hotel) ”, data in the format (3: <charge>, $ cheap1) is registered in the ambiguous word storage unit 9. When the command input from the command conversion unit 2 includes an ambiguous word meaning indicator, the estimated value adaptation unit 11 first registers the ambiguous word meaning indicator in the ambiguous word storage unit 9 in the format described above.
【００２９】次に、推定値適応部１１は、上記コマンド
に対する対話管理部５の応答が利用者に対して通知され
た後に、この応答に対する利用者の発話内容から、曖昧
語記憶部９に登録された曖昧語の意味標識に対する推定
値を推定する。次に推定の方法を具体例とともに説明す
る。例えば、利用者の発話が「横浜で安いホテルを教え
て下さい」であって、これに対する対話管理部５の応答
が、「横浜の安いホテルは、Ａホテル４５００円、Ｂホ
テル５５００円、Ｃホテル６０００円、があります」で
あったとする。この応答に対する利用者の発話は、例え
ば、以下の３通りが考えられる。 （１）「１００００円くらいが良いのですが」 （２）「もう少し高くても構いません」 （３）「Ｃホテルの最寄駅はどこですか」Next, after the response of the dialog management unit 5 to the command is notified to the user, the estimated value adaptation unit 11 registers the response in the ambiguous word storage unit 9 based on the contents of the user's utterance to the response. The estimated value for the meaning marker of the obtained ambiguous word is estimated. Next, an estimation method will be described with a specific example. For example, the user's utterance is "Please tell me a cheap hotel in Yokohama", and the response of the dialogue management unit 5 is "The cheap hotel in Yokohama is A hotel 4500 yen, B hotel 5500 yen, C hotel. There is 6,000 yen. " The user's utterance in response to this response may be, for example, the following three types. (1) "I recommend about 10000 yen" (2) "It's fine if it's a little higher" (3) "Where is the nearest station of C Hotel"
【００３０】（１）は、応答中に示された金額を受け入
れられず、利用者が明示的に自分が想定している金額を
表明している場合である。このときは、「安い」という
曖昧語の推定値は、入力されたコマンド中の１００００
円程度であると推定できる。（２）は、応答中に示され
た金額を受け入れられず、利用者がシステムに対し再
度、検索要求の意図の発話をしている場合である。この
ときは、入力されたコマンド中の「高い」という別の曖
昧語により、「安い」という曖昧語の推定値は、提示し
た金額の最高値である６０００円より高い金額であると
推定できる。（３）は、発話の意図が、項目＜料金＞以
外の項目＜最寄駅＞を尋ねる＜項目質問＞の意図である
ことから、応答中に示された金額のうち、Ｃホテルの金
額を受け入れたと考えられる。そこで、「安い」という
曖昧語の推定値は、６０００円程度であると推定でき
る。The case (1) is a case where the amount indicated in the response cannot be accepted and the user expressly expresses the amount assumed by the user. At this time, the estimated value of the ambiguous word "cheap" is 10000 in the input command.
It can be estimated that it is about a circle. (2) is a case where the amount indicated in the response cannot be accepted and the user speaks again to the system with the intention of the search request. At this time, the estimated value of the ambiguous word "cheap" can be estimated to be higher than the maximum value of the presented amount of 6000 yen by another ambiguous word "high" in the input command. (3) indicates that the intention of the utterance is the intention of <item question> for asking for the item <nearest station> other than the item <charge>, so the amount of C hotel among the amounts indicated in the response is It is considered accepted. Therefore, the estimated value of the ambiguous word “cheap” can be estimated to be about 6,000 yen.
【００３１】以上のような推定を行なうために、推定知
識記憶部１０は、応答履歴記憶部４に記憶された応答意
味表現と、コマンド変換部２から入力されたコマンドと
の関係から判定するための推定知識を曖昧語の推定値と
して記憶する。推定値適応部１１は、入力されたコマン
ド及び応答履歴記憶部４の応答の意味表現を参照して、
推定知識記憶部１０の推定知識に基づいて、曖昧語の推
定値を決定する。これより、利用者識別子に対応した推
定値情報記憶部７の推定値情報を更新して学習し、学習
の対象とした曖昧語の意味標識を曖昧語記憶部９から削
除する。図４に推定値情報記憶部７に記憶されたデータ
構造を示す。In order to perform the above estimation, the estimated knowledge storage unit 10 determines the response knowledge expression from the relationship between the response meaning expression stored in the response history storage unit 4 and the command input from the command conversion unit 2. Is stored as an estimated value of the ambiguous word. The estimated value adaptation unit 11 refers to the input command and the semantic expression of the response in the response history storage unit 4, and
The estimated value of the ambiguous word is determined based on the estimated knowledge in the estimated knowledge storage unit 10. Thus, the estimated value information in the estimated value information storage unit 7 corresponding to the user identifier is updated and learned, and the meaning marker of the vague word targeted for learning is deleted from the vague word storage unit 9. FIG. 4 shows a data structure stored in the estimated value information storage unit 7.
【００３２】推定知識記憶部１０に記憶された推定知識
は、例えば、上記（１）〜（３）の場合分けができるよ
うな条件判定部を持つ知識として、ｉｆ〜ｔｈｅｎ〜形
式のルールで以下のように記述する。 （１）ｉｆ（応答履歴記憶部４の応答中に＜検索結果提
示＞の項目値Ａが存在する ａｎｄ 現在のコマンド中に
＜意図：項目値表明＞とともに項目値Ｂが存在する）ｔ
ｈｅｎ（推定値を項目値Ｂとする） （２）ｉｆ（応答履歴記憶部４の応答中に＜検索結果提
示＞の項目値Ａが存在する ａｎｄ 現在のコマンド中に
＜意図：検索要求＞とともに項目値Ａに対応する項目に
関する曖昧語の意味標識が存在する）ｔｈｅｎ（次のコ
マンド入力を待つ） （３）ｉｆ（応答履歴記憶部４の応答中に＜検索結果提
示＞の項目値Ａが存在する ａｎｄ 現在のコマンド中に
項目値Ａと対応しない項目に関する＜意図：項目質問＞
とともに直前の応答中の対象名が存在する）ｔｈｅｎ
（推定値を直前の応答中の対象名に対応する項目値Ａと
する）The presumed knowledge stored in the presumed knowledge storage unit 10 is, for example, a knowledge having a condition judging unit that can be divided into the above cases (1) to (3). Describe as follows. (1) if (the item value A of <search result presentation> exists in the response of the response history storage unit 4 and and the item value B exists along with <intention: item value assertion> in the current command) t
hen (the estimated value is assumed to be the item value B) (2) if (the item value A of <presentation of search result> exists in the response of the response history storage unit 4) and <intention: search request> in the current command There is an ambiguous word meaning indicator related to the item corresponding to item value A) then (waiting for next command input) (3) if (item value A of <search result presentation> during response of response history storage unit 4) Exists and regarding items that do not correspond to item value A in the current command <intention: item question>
And the subject name in the previous response exists)
(The estimated value is the item value A corresponding to the target name in the immediately preceding response.)
【００３３】推定値適応部１１は、上記のようにして求
めた推定値を推定値情報記憶部７における推定値情報と
して記録する。推定値情報は、例えば、各項目の各曖昧
語の意味標識に関して、各推定値の頻度情報を記録して
おけばよい。The estimated value adapting section 11 records the estimated value obtained as described above as estimated value information in the estimated value information storage section 7. As the estimated value information, for example, frequency information of each estimated value may be recorded for the meaning marker of each ambiguous word of each item.
【００３４】以上のように上記実施の形態１によれば、
利用者の曖昧語を含む自然言語の入力に対して、意図、
項目、及び項目値からなる表現でコマンドに変換し、曖
昧語に対応する意味標識の推定値を決定してコマンドと
ともに出力することにより、効率的かつ柔軟な検索がで
きるという効果が得られる。また、曖昧な語が表わす値
を利用者の発話履歴から学習して、利用者に応じて自動
的に設定して翻訳することにより、情報検索の効率化、
及び利用者の感覚に合致した自然な情報提示を行なうこ
とができ、利用者の利便性を向上させることができると
いう効果が得られる。As described above, according to the first embodiment,
For the input of natural language including ambiguous words of the user, intention,
By converting the expression into a command using an expression consisting of an item and an item value, determining an estimated value of the meaning indicator corresponding to the ambiguous word, and outputting the determined value together with the command, an effect that an efficient and flexible search can be performed is obtained. Also, by learning the value represented by the ambiguous word from the user's utterance history and automatically setting and translating it according to the user, the efficiency of information retrieval is improved,
In addition, it is possible to perform natural information presentation that matches the user's feeling, and it is possible to obtain an effect that the convenience of the user can be improved.
【００３５】なお、上記実施の形態１において、複数の
検索対象がある場合には、項目＜料金＞をそれぞれ別な
項目として定義する。例えば、検索項目がホテル及びレ
ストランである場合には、ホテルは、Ｓｅａｒｃｈ［ｈ
ｏｔｅｌ］：＜料金（ホテル）＞＝＄ｃｈｅａｐ ｈｏ
ｔｅｌとなり、レストランは、Ｓｅａｒｃｈ［ｒｅｓｔ
ａｕｒａｎｔ］：＜料金（レストラン）＞＝＄ｃｈｅａ
ｐ ｒｅｓｔａｕｒａｎｔとなる。In the first embodiment, when there are a plurality of search targets, the item <charge> is defined as a different item. For example, if the search item is a hotel and a restaurant, the hotel searches for Search [h
otel]: <Price (Hotel)> = ¥ cheap ho
tel, and the restaurant is Search [rest]
aurant]: <fee (restaurant)> = $ chea
pre-resturant.
【００３６】実施の形態２．図５はこの発明の実施の形
態２における音声対話システムの機能ブロック構成図で
あり、図において、１２は補間モデル記憶部（補間モデ
ル記憶手段）、１３は推定値補間部（推定値補間手段）
である。他の構成は図１に示した実施の形態１の構成と
同じであり、同一の符号で表されている。次に動作につ
いて説明する。この実施の形態２は、利用者が対話シス
テムを利用した回数が少ない場合に、推定値情報記憶部
７に記憶される推定値情報の学習において、推定値情報
が未学習である曖昧語の意味標識に対して、他の学習済
の曖昧語の推定値情報を用いて、未学習の曖昧語の意味
標識の推定値を補間して算出するものである。Embodiment 2 FIG. 5 is a functional block diagram of a speech dialogue system according to Embodiment 2 of the present invention. In the figure, reference numeral 12 denotes an interpolation model storage unit (interpolation model storage unit), and 13 denotes an estimated value interpolation unit (estimated value interpolation unit).
It is. Other configurations are the same as those of the first embodiment shown in FIG. 1 and are denoted by the same reference numerals. Next, the operation will be described. According to the second embodiment, when the number of times the user has used the dialogue system is small, in learning the estimated value information stored in the estimated value information storage unit 7, the meaning of an ambiguous word whose estimated value information has not been learned is used. For the sign, the estimated value of the semantic sign of the unlearned ambiguous word is calculated by interpolating using the estimated value information of the other learned ambiguous word.
【００３７】補間モデル記憶部１２は、曖昧語の意味標
識と、該意味標識に対応する推定値との関係を関数とし
て規定し、補間モデルとして記憶する。補間モデルとし
て用いる上記関数は、曖昧語の意味標識が与えられたと
きにその推定値を補間して算出できるものであればよ
い。例えば、図２に示すように、＜料金＞という同一項
目に対する複数の曖昧語の意味標識として、＄ｃｈｅａ
ｐｅｓｔ（曖昧語：できるだけ安い）、＄ｃｈｅａｐ１
（曖昧語：安い）、＄ｃｈｅａｐ２（曖昧語：できれば
安い）、＄ｎｏｔ＿ｓｏ＿ｅｘｐ（曖昧語：あまり高く
ない）、＄ｅｘｐ（曖昧語：少し高くても良い）、など
が定義されている場合、これらの推定値を順に、ｖ１、
ｖ２、ｖ３、ｖ４、ｖ５、とすれば、ｖ１＝ｖ２−１０
００、ｖ１＝ｖ３−２０００、ｖ１＝ｖ４−３０００、
ｖ１＝ｖ５−４０００、などのように、推定値同士の差
分を規定する関数を記憶しておく。The interpolation model storage unit 12 defines a relationship between a meaning marker of an ambiguous word and an estimated value corresponding to the meaning marker as a function, and stores the relationship as an interpolation model. The function used as the interpolation model may be any function that can be calculated by interpolating the estimated value when the meaning indicator of the vague word is given. For example, as shown in FIG. 2, as a meaning indicator of a plurality of ambiguous words for the same item <charge>, $ chea
vest (ambiguity: as cheap as possible), @ cheap1
(Ambiguous words: cheap), ＄ cheap2 (ambiguous words: cheap if possible), ＄ not_so_exp (ambiguous words: not very high), ＄ exp (ambiguous words: may be a little high), etc. Are estimated in order, v1,
If v2, v3, v4, v5, v1 = v2-10
00, v1 = v3-2000, v1 = v4-3000,
A function that defines the difference between the estimated values, such as v1 = v5-4000, is stored.
【００３８】推定値補間部１３は、曖昧語翻訳部８から
の利用者識別子及び曖昧語の意味標識を入力とし、推定
値情報記憶部７に記憶されている利用者識別子に対応し
た推定値情報を参照して、入力された曖昧語の意味標識
に対する推定値情報が未学習の場合に、補間モデル記憶
部１２の補間モデルを用いて、学習済の曖昧語の意味標
識に対する推定値情報から、未学習の該意味標識の推定
値を算出して曖昧語翻訳部８へ出力する。例えば、曖昧
語の意味標識＄ｃｈｅａｐｅｓｔ（曖昧語：できるだけ
安い）の推定値ｖ１が未学習であり、＄ｃｈｅａｐ１
（曖昧語：安い）の推定値ｖ２が学習済であって、ｖ２
＝６０００であるとする。このとき、推定値補間部１３
は、補間モデル記憶部１２に記憶された上記推定値同士
の差分を規定する関数を参照して、ｖ１＝ｖ２−１００
０＝５０００、のように、未学習の推定値ｖ１を算出す
る。The estimated value interpolating unit 13 receives the user identifier from the ambiguous word translating unit 8 and the meaning marker of the ambiguous word as input, and outputs the estimated value information corresponding to the user identifier stored in the estimated value information storing unit 7. With reference to, when the estimated value information for the input meaning marker of the ambiguous word is not yet learned, the estimated value information for the meaning marker of the learned ambiguous word is obtained using the interpolation model of the interpolation model storage unit 12. An estimated value of the unlearned meaning indicator is calculated and output to the ambiguous word translating unit 8. For example, the estimated value v1 of the meaning marker of an ambiguous word ＄ cheapest (ambiguous word: as cheap as possible) is unlearned, and ＄ cheap1
The estimated value v2 of (ambiguous word: cheap) has been learned and v2
= 6000. At this time, the estimated value interpolation unit 13
Is referred to as a function defining the difference between the estimated values stored in the interpolation model storage unit 12, and v1 = v2-100
An unlearned estimated value v1 is calculated as 0 = 5000.
【００３９】以上のように、上記実施の形態２によれ
ば、未学習の曖昧語の推定値を学習済の曖昧語の推定値
情報から補間して算出できるようにしたので、利用者が
対話システムを利用した回数が少ない場合でも、曖昧語
の項目値を推定して、情報検索の効率化、及び利用者の
感覚に合致した自然な情報提示を行なうことができ、利
用者の利便性を向上させることができるという効果が得
られる。As described above, according to the second embodiment, the estimated value of the unlearned ambiguous word can be calculated by interpolating from the estimated value information of the learned ambiguous word. Even if the number of times the system has been used is small, it is possible to estimate the item values of the vague words, to improve the efficiency of information retrieval, and to present natural information that matches the user's sense, thereby improving user convenience. The effect of being able to improve is obtained.
【００４０】実施の形態３．図６はこの発明の実施の形
態３における音声対話システムの機能ブロック構成図で
あり、図において、１４は全利用者推定値情報記憶部
（全利用者推定値情報記憶手段）、１５は推定値選択部
（推定値選択手段）である。他の構成については図１に
示した実施の形態１の構成と同じであり、同一の符号で
表されている。Embodiment 3 FIG. 6 is a functional block diagram of a voice dialogue system according to Embodiment 3 of the present invention. In FIG. 6, reference numeral 14 denotes an all-user estimated value information storage unit (all-user estimated value information storage means); A selector (estimated value selecting means); Other configurations are the same as those of the first embodiment shown in FIG. 1, and are denoted by the same reference numerals.
【００４１】次に動作について説明する。この実施の形
態３は、利用者が対話システムを利用した回数が少ない
場合に、推定値情報記憶部７に記憶される推定値情報が
未学習である曖昧語の意味標識に対して、推定値情報の
一致度が高い他の利用者の学習済の曖昧語の推定値情報
を用いて、未学習の曖昧語の意味標識を推定して算出す
るものである。Next, the operation will be described. In the third embodiment, when the number of times the user has used the dialogue system is small, the estimated value information stored in the estimated value The semantic marker of the unlearned ambiguous word is estimated and calculated using the estimated value information of the learned ambiguous word of another user having a high degree of matching of the information.
【００４２】全利用者推定値情報記憶部１４は、全ての
利用者に対する推定値情報を利用者識別子に対応して記
憶する。全利用者推定値情報記憶部１４におけるデータ
構造は、図４に示したデータ構造にさらに利用者識別子
を付加したものになる。推定値選択部１５は、曖昧語翻
訳部８からの利用者識別子及び曖昧語の意味標識を入力
とし、推定値情報記憶部７に記憶されている利用者識別
子に対応した推定値情報を参照して、入力された曖昧語
の意味標識に対する推定値情報が未学習の場合に、全利
用者推定値情報記憶部１４を参照する。そして、現在シ
ステムを利用している利用者Ａの推定値情報と、他の利
用者Ｂの推定値情報との、推定値情報の一致度を算出す
る。一致度は、例えば、利用者Ａ、利用者Ｂともに学習
済の曖昧語の推定値を比較し、推定値の差がある一定の
範囲内であれば、その曖昧語の推定値が一致していると
し、一致した曖昧語の数を一致度として定義する。The all-user estimated value information storage unit 14 stores estimated value information for all users corresponding to user identifiers. The data structure in the all-user estimated value information storage unit 14 is obtained by further adding a user identifier to the data structure shown in FIG. The estimated value selecting unit 15 receives the user identifier and the ambiguous word meaning indicator from the ambiguous word translation unit 8 and refers to the estimated value information corresponding to the user identifier stored in the estimated value information storage unit 7. If the estimated value information for the input meaning tag of the ambiguous word has not been learned, the total user estimated value information storage unit 14 is referred to. Then, the degree of coincidence of the estimated value information between the estimated value information of the user A currently using the system and the estimated value information of the other user B is calculated. The degree of coincidence is determined, for example, by comparing the estimated values of the learned ambiguous words for both user A and user B, and if the difference between the estimated values is within a certain range, the estimated values of the ambiguous words match. And the number of matching vague words is defined as the degree of matching.
【００４３】推定値選択部１５は、全利用者推定値情報
記憶部１４に記憶された全ての利用者に対する推定値情
報を参照して、利用者Ａで未学習である曖昧語の推定値
情報を有する利用者の内、利用者Ａとの一致度が最も高
い利用者Ｃを選択し、利用者Ｃの学習済の曖昧語の推定
値情報を、利用者Ａの未学習の意味標識の推定値として
曖昧語翻訳部８へ出力する。The estimated value selecting unit 15 refers to the estimated value information for all users stored in the all user estimated value information storage unit 14 and estimates the unlearned ambiguous word of the user A. Of the users having the highest matching degree with the user A are selected, and the estimated value information of the learned ambiguous words of the user C is estimated from the user A's unlearned meaning markers. The value is output to the ambiguous word translator 8.
【００４４】以上のように、上記実施の形態３によれ
ば、未学習の曖昧語の推定値を、推定値情報の一致度が
高い他の利用者の推定値で代用するようにしたので、利
用者が対話システムを利用した回数が少ない場合でも、
曖昧語の推定値を推定して、情報検索の効率化、及び利
用者の感覚に合致した自然な情報提示を行なうことがで
き、利用者の利便性を向上させることができるという効
果が得られる。As described above, according to the third embodiment, the estimated value of the unlearned ambiguous word is substituted by the estimated value of another user having a high degree of coincidence of the estimated value information. Even if the user has used the dialogue system only a few times,
By estimating the estimated value of an ambiguous word, it is possible to improve the efficiency of information search and to perform natural information presentation that matches the user's sense, thereby improving the user's convenience. .
【００４５】なお、上記各実施の形態においては、音声
対話システムの発明について説明したが、この発明の音
声対話システム及び電話回線を含む統合的なコンピュー
タシステムを構築して、電話回線を介して入力された利
用者すなわち顧客の曖昧語を含む自然言語を理解して、
顧客が要望する情報を安い料金で提供するビジネスを展
開することができる。その他、例えば、受付、注文、予
約などの各種サービス代行や、利用者が要求する情報の
提供を行なう電話音声自動応答装置にもこの発明の音声
対話システムを適用することにより著しい効果が得られ
る。あるいは、発明の音声対話システムを適用すること
により、顧客の曖昧語を含む自然言語を理解する自動販
売機を実現できるという効果が得られる。In each of the above embodiments, the invention of the voice dialogue system has been described. However, an integrated computer system including the voice dialogue system of the present invention and a telephone line is constructed, and input is made via the telephone line. Understand the natural language including the ambiguous word of the user or customer,
Businesses that provide information requested by customers at low rates can be developed. In addition, a remarkable effect can be obtained by applying the voice interactive system of the present invention to, for example, a telephone automatic voice response apparatus for performing various services such as reception, order, reservation, and providing information requested by a user. Alternatively, by applying the voice dialogue system of the present invention, there is obtained an effect that a vending machine that understands a natural language including ambiguous words of a customer can be realized.
【００４６】[0046]
【発明の効果】以上のように、この発明によれば、音声
対話システムを、対話システム動作に対応して定義され
たコマンド意図、対話システム動作のパラメータの種類
を定義した項目、及び項目に対応する値である項目値か
らなる表現を対話システムのコマンドとし、自然言語を
コマンドへ変換するための変換知識をコマンド知識とし
て記憶するコマンド知識記憶手段と、自然言語において
項目値へ一意に変換できない語を曖昧語とし、曖昧語、
曖昧語の項目、及び曖昧語に対応する意味標識を曖昧語
辞書として記憶する曖昧語辞書記憶手段と、曖昧語辞書
記憶手段に記憶された曖昧語辞書を参照して、利用者が
入力した自然言語に含まれる曖昧語を曖昧語に対応する
意味標識に置換して、曖昧語の項目と意味標識の対を作
成し、コマンド知識記憶手段に記憶されたコマンド知識
を参照して、入力された自然言語を、曖昧語の項目と意
味標識の対を含んだコマンドに変換するコマンド変換手
段と、曖昧語に対応する意味標識の値を推定するための
推定値情報を利用者を特定する利用者識別子とともに記
憶する推定値情報記憶手段と、コマンド変換手段から入
力される曖昧語の項目と意味標識の対を含んだコマンド
に対し、推定値情報記憶手段に記憶された利用者識別子
に対応した推定値情報を参照して、曖昧語に対応する意
味標識の推定値を決定してコマンドとともに出力する曖
昧語翻訳手段とを備えるように構成したので、利用者の
曖昧語を含む自然言語の入力に対して、意図、項目、及
び項目値からなる表現でコマンドに変換し、曖昧語に対
応する意味標識の推定値を決定してコマンドとともに出
力することにより、効率的かつ柔軟な検索ができるとい
う効果がある。As described above, according to the present invention, the speech dialogue system is adapted to correspond to the command intention defined corresponding to the dialogue system operation, the item defining the parameter type of the dialogue system operation, and the item. Command knowledge storage means for storing, as command knowledge, a conversion expression for converting a natural language into a command using an expression consisting of item values which are values to be executed, and a word which cannot be uniquely converted to an item value in a natural language Is an ambiguous word, an ambiguous word,
The ambiguous word dictionary storage means for storing the ambiguous word items and the meaning markers corresponding to the ambiguous words as the fuzzy word dictionary, and the natural language input by the user with reference to the fuzzy word dictionary stored in the fuzzy word dictionary storage means. An ambiguous word included in the language is replaced with a semantic indicator corresponding to the ambiguous word, a pair of the ambiguous word item and the semantic indicator is created, and the pair is input with reference to the command knowledge stored in the command knowledge storage means. Command conversion means for converting a natural language into a command including a pair of an ambiguous word item and a semantic indicator, and a user who specifies estimated value information for estimating a value of the semantic indicator corresponding to the ambiguous word Estimation value information storage means stored with the identifier, and estimation corresponding to the user identifier stored in the estimation value information storage means for a command containing a pair of an ambiguous word item and a meaning marker input from the command conversion means. value And an ambiguous word translating means for determining an estimated value of a semantic indicator corresponding to the ambiguous word and outputting the same together with the command, so that the user can input natural language including the ambiguous word. Thus, by converting into a command using an expression consisting of an intention, an item, and an item value, determining an estimated value of a meaning indicator corresponding to an ambiguous word, and outputting it together with the command, an effect that efficient and flexible search can be performed. is there.
【００４７】この発明における音声対話システムにおい
て、曖昧語の意味標識と、該意味標識に対応する推定値
との関係を関数として規定し、補間モデルとして記憶し
た補間モデル記憶手段と、曖昧語翻訳手段からの利用者
識別子及び曖昧語の意味標識を入力とし、利用者識別子
に対応した推定値情報における曖昧語のうち、入力され
た意味標識の推定値情報が未学習である曖昧語に対し
て、補間モデル記憶手段の補間モデルを用いて、学習済
の曖昧語の意味標識に対する推定値情報から、未学習の
意味標識の推定値を算出して曖昧語翻訳手段へ出力する
推定値補間手段とを備えるように構成したので、利用者
が対話システムを利用した回数が少ない場合でも、曖昧
語の項目値を推定して、情報検索の効率化、及び利用者
の感覚に合致した自然な情報提示を行なうことができ、
利用者の利便性を向上させることができるという効果が
ある。In the speech dialogue system according to the present invention, an interpolated model storage means for defining a relation between a meaning marker of an ambiguous word and an estimated value corresponding to the meaning marker as a function and storing the function as an interpolation model, and an ambiguous word translation means The user identifier and the meaning sign of the ambiguous word are input, and among the ambiguous words in the estimated value information corresponding to the user identifier, for the ambiguous word whose estimated value information of the inputted meaning sign is unlearned, An interpolating model stored in the interpolated model storage means, the estimated value information of the unlearned semantic sign from the estimated value information for the semantic sign of the learned ambiguous word, and an estimated value interpolating means for calculating and outputting to the ambiguous word translating means. Even if the number of times that the user has used the dialogue system is small, the item value of the vague word is estimated to improve the efficiency of information retrieval and to match the user's sense. The such information presentation can be carried out,
There is an effect that the convenience of the user can be improved.
【００４８】この発明における音声対話システムにおい
て、全ての利用者に対する推定値情報を記憶する全利用
者推定値情報記憶手段と、曖昧語翻訳手段からの利用者
識別子及び曖昧語の意味標識を入力とし、利用者識別子
に対応した推定値情報における曖昧語のうち、入力され
た意味標識の推定値情報が未学習である曖昧語に対し
て、全利用者推定値情報記憶手段に記憶された全ての利
用者に対する推定値情報を参照して、学習済の曖昧語の
意味標識に対する推定値情報との一致度が高い他の利用
者の推定値情報を利用し、未学習の意味標識の推定値を
選択して曖昧語翻訳手段へ出力する推定値選択手段とを
備えたように構成したので、利用者が対話システムを利
用した回数が少ない場合でも、曖昧語の推定値を推定し
て、情報検索の効率化、及び利用者の感覚に合致した自
然な情報提示を行なうことができ、利用者の利便性を向
上させることができる効果がある。In the speech dialogue system according to the present invention, all user estimated value information storage means for storing estimated value information for all users, and user identifiers and ambiguous word meaning indicators from ambiguous word translation means are input. Of the ambiguous words in the estimated value information corresponding to the user identifier, all the ambiguous words for which the input estimated value information of the meaning sign is unlearned are stored in the all user estimated value information storage means. Referring to the estimated value information for the user, the estimated value of the unlearned semantic marker is calculated using the estimated value information of another user having a high degree of matching with the estimated value information for the semantic marker of the learned vague word. Since it is configured to include an estimation value selection means for selecting and outputting to the fuzzy word translation means, even when the number of times the user has used the dialogue system is small, the estimation value of the fuzzy word is estimated and the information retrieval is performed. Efficiency , And can be performed natural information presentation that matches the feeling of the user, there is an effect that it is possible to improve the convenience of the user.
【００４９】この発明における音声対話システムにおい
て、項目及び項目値が付与された検索対象データの集合
を記憶するデータベースと、入力されたコマンドに対応
して、所定の対話システム動作を実行してシステムと利
用者との対話を管理するとともにデータベースを検索
し、利用者へ通知する応答文の意味内容を表わす応答意
味表現を生成する対話管理手段とを備えるように構成し
たので、利用者の曖昧語を含む自然言語の入力に対し
て、意図、項目、及び項目値からなる表現でコマンドに
変換してデータベースを検索し、利用者の入力に適応し
た応答ができるという効果がある。In the voice dialogue system according to the present invention, a database for storing a set of search target data to which items and item values are assigned, and a predetermined dialogue system operation are executed in response to an inputted command to execute the system. Dialog management means for managing the dialogue with the user, searching the database, and generating a response semantic expression representing the meaning of the response sentence notified to the user. With respect to the input of the natural language including the input, there is an effect that a database can be searched by converting the input into a command using an expression including an intention, an item, and an item value, and a response adapted to the input of the user can be performed.
【００５０】この発明における音声対話システムにおい
て、対話管理手段で生成された応答意味表現を、対話の
開始からの応答順に記憶する応答履歴記憶手段と、推定
値の学習対象となる曖昧語の意味標識を、曖昧語の項目
とともに、対話の開始からの入力順に記憶する曖昧語記
憶手段と、曖昧語の意味標識の推定値を、応答履歴記憶
手段に記憶された応答意味表現と、コマンド変換手段か
ら入力されたコマンドとの関係から判定するための知識
を推定知識として記憶する推定知識記憶手段と、コマン
ド変換手段から入力されたコマンドに曖昧語の意味標識
が含まれる場合に曖昧語記憶手段へ意味標識を登録し、
推定知識記憶手段の推定知識を用いて、入力されたコマ
ンド及び応答履歴記憶手段の応答から、登録された曖昧
語の意味標識に対する推定値を推定し、利用者識別子に
対応した推定値情報記憶手段の推定値情報を更新して学
習し、学習の対象とした曖昧語の意味標識を曖昧語記憶
手段から削除する推定値適応手段とを備えるように構成
したので、曖昧な語が表わす値を利用者の発話履歴から
学習して、利用者に応じて自動的に設定して翻訳するこ
とにより、情報検索の効率化、及び利用者の感覚に合致
した自然な情報提示を行なうことができ、利用者の利便
性を向上させることができるという効果がある。In the voice dialogue system according to the present invention, response history storage means for storing the response meaning expressions generated by the dialogue management means in the order of responses from the start of the dialogue, and semantic markers of ambiguous words for which the estimated value is to be learned With the ambiguous word item, in the order of input from the start of the dialogue, and the estimated value of the meaning marker of the ambiguous word is obtained from the response semantic expression stored in the response history storage means and the command conversion means. Estimated knowledge storage means for storing knowledge for determining from the relationship with the input command as estimated knowledge, and meaning to the ambiguous word storage means when the command input from the command conversion means includes an ambiguous word meaning indicator Register the sign,
Using the estimated knowledge of the estimated knowledge storage means, an estimated value for the registered meaning marker of the ambiguous word is estimated from the input command and the response of the response history storage means, and the estimated value information storage means corresponding to the user identifier And updating the estimated value information of, and deleting the meaning indicator of the ambiguous word targeted for learning from the ambiguous word storage means, so that the value represented by the ambiguous word is used. By learning from the utterance history of the user and automatically setting and translating according to the user, it is possible to improve the efficiency of information retrieval and present natural information that matches the user's sense, There is an effect that the convenience of the person can be improved.
【図１】 この発明の実施の形態１における音声対話シ
ステムの機能ブロック構成図である。FIG. 1 is a functional block configuration diagram of a voice interaction system according to a first embodiment of the present invention.
【図２】 この発明の各実施の形態における曖昧語辞書
記憶部に記憶される項目、曖昧語、及び意味標識の対応
関係の例を示す図である。FIG. 2 is a diagram illustrating an example of a correspondence relationship between an item, an ambiguous word, and a meaning marker stored in an ambiguous word dictionary storage unit according to each embodiment of the present invention.
【図３】 この発明の各実施の形態におけるデータベー
スに記憶される検索対象データの例を示す図である。FIG. 3 is a diagram showing an example of search target data stored in a database according to each embodiment of the present invention.
【図４】 この発明の実施の形態１における推定情報記
憶部に記憶されるデータ構造を示す図である。FIG. 4 is a diagram showing a data structure stored in an estimated information storage unit according to the first embodiment of the present invention.
【図５】 この発明の実施の形態２における音声対話シ
ステムの機能ブロック構成図である。FIG. 5 is a functional block configuration diagram of a voice interaction system according to a second embodiment of the present invention.
【図６】 この発明の実施の形態３における音声対話シ
ステムの機能ブロック構成図である。FIG. 6 is a functional block configuration diagram of a voice interaction system according to a third embodiment of the present invention.
【符号の説明】 １ コマンド知識記憶部（コマンド知識記憶手段）、２
コマンド変換部（コマンド変換手段）、３ データベ
ース、４ 応答履歴記憶部（応答履歴記憶手段）、５
対話管理部（対話管理手段）、６ 曖昧語辞書記憶部
（曖昧語辞書記憶手段）、７ 推定値情報記憶部（推定
値情報記憶手段）、８ 曖昧語翻訳部（曖昧語翻訳手
段）、９ 曖昧語記憶部（曖昧語記憶手段）、１０ 推
定知識記憶部（推定知識記憶手段）、１１ 推定値適応
部（推定値適応手段）、１２ 補間モデル記憶部（補間
モデル記憶手段）、１３ 推定値補間部（推定値補間手
段）、１４ 全利用者推定値情報記憶部（全利用者推定
値情報記憶手段）、１５ 推定値選択部（推定値選択手
段）。[Description of Signs] 1 Command knowledge storage unit (command knowledge storage means), 2
Command conversion unit (command conversion unit), 3 database, 4 response history storage unit (response history storage unit), 5
Dialogue management unit (dialogue management unit), 6 Ambiguous word dictionary storage unit (ambiguous word dictionary storage unit), 7 Estimated value information storage unit (estimated value information storage unit), 8 Fuzzy word translation unit (ambiguous word translation unit), 9 Ambiguous word storage unit (ambiguous word storage unit), 10 estimated knowledge storage unit (estimated knowledge storage unit), 11 estimated value adaptation unit (estimated value adaptation unit), 12 interpolation model storage unit (interpolation model storage unit), 13 estimated value Interpolation unit (estimated value interpolation means), 14 total user estimated value information storage unit (all user estimated value information storage means), 15 estimated value selection unit (estimated value selection means).
───────────────────────────────────────────────────── フロントページの続き (51)Int.Cl.7 識別記号 ＦＩ テーマコート゛(参考） Ｇ１０Ｌ 15/18 Ｇ１０Ｌ 3/00 ５３７Ｚ 15/22 ５７１Ｕ──────────────────────────────────────────────────続 き Continued on the front page (51) Int.Cl.7 Identification symbol FI Theme coat ゛ (Reference) G10L 15/18 G10L 3/00 537Z 15/22 571U
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| JP2000211551AJP3949356B2 (en) | 2000-07-12 | 2000-07-12 | Spoken dialogue system |
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP2000211551AJP3949356B2 (en) | 2000-07-12 | 2000-07-12 | Spoken dialogue system |
| Publication Number | Publication Date |
|---|---|
| JP2002024212Atrue JP2002024212A (en) | 2002-01-25 |
| JP3949356B2 JP3949356B2 (en) | 2007-07-25 |
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP2000211551AExpired - Fee RelatedJP3949356B2 (en) | 2000-07-12 | 2000-07-12 | Spoken dialogue system |
| Country | Link |
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| JP (1) | JP3949356B2 (en) |
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