研究者詳細 - 髙梨克也

論文 - 髙梨克也

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An attentive listening system for autonomous android erica: Comparative evaluation with human attentive listeners 査読

Inoue K., Lala D., Yamamoto K., Nakamura S., Takanashi K., Kawahara T.

Transactions of the Japanese Society for Artificial Intelligence 36 ( 5 ) 2021年1月

記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：Transactions of the Japanese Society for Artificial Intelligence

An attentive listening system for autonomous android ERICA is presented. Our goal is to realize a human-like natural attentive listener for elderly people. The proposed system generates listener responses: backchannels, repeats, elaborating questions, assessments, and generic responses. The system incorporates speech processing using a microphone array and real-time dialogue processing including continuous backchannel prediction and turn-taking prediction. In this study, we conducted a dialogue experiment with elderly people. The system was compared with a WOZ system where a human operator played the listener role behind the robot. As a result, the system showed comparable scores in basic skills of attentive listening, such as easy to talk, seriously listening, focused on the talk, and actively listening. It was also found that there is still a gap between the system and the human (WOZ) for high-level attentive listening skills such as dialogue understanding, showing interest, and empathy towards the user.

DOI： 10.1527/tjsai.36-5_H-L51

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85114196962&origin=inward

A Character Expression Model Affecting Spoken Dialogue Behaviors

Kenta Yamamoto, Koji Inoue, Shizuka Nakamura, Katsuya Takanashi, Tatsuya Kawahara

Lecture Notes in Electrical Engineering 704 3 - 13 2021年

掲載種別：研究論文（国際会議プロシーディングス）

We address character (personality) expression for a spoken dialogue system in order to accommodate it in particular dialogue tasks and social roles. While conventional studies investigated controlling the linguistic expressions, we focus on spoken dialogue behaviors to express systems’ characters. Specifically, we investigate spoken dialogue behaviors such as utterance amount, backchannel frequency, filler frequency, and switching pause length in order to express three character traits: extroversion, emotional instability, and politeness. In this study, we evaluate this model with a natural spoken dialogue corpus. The results reveal that this model expresses reasonable characters according to the dialogue tasks and the participant roles. Furthermore, it is also shown that this model is able to express different characters among participants given the same role. A subjective experiment demonstrated that subjects could perceive the characters expressed by the model.

DOI： 10.1007/978-981-15-8395-7_1

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A Job Interview Dialogue System with Autonomous Android ERICA

Koji Inoue, Kohei Hara, Divesh Lala, Shizuka Nakamura, Katsuya Takanashi, Tatsuya Kawahara

Lecture Notes in Electrical Engineering 714 291 - 297 2021年

掲載種別：論文集(書籍)内論文出版者・発行元：Springer

We demonstrate a job interview dialogue with the autonomous android ERICA which plays the role of an interviewer. Conventional job interview dialogue systems ask only pre-defined questions. The job interview system of ERICA generates follow-up questions based on the interviewee’s response on the fly. The follow-up questions consist of two kinds of approaches: selection-based and keyword-based. The first type question is based on selection from a pre-defined question set, which can be used in many cases. The second type of question is based on a keyword extracted from the interviewee’s response, which digs into the interviewee’s response dynamically. These follow-up questions contribute to realizing natural and trained dialogue.

DOI： 10.1007/978-981-15-9323-9_25

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その他リンク： https://dblp.uni-trier.de/db/conf/iwsds/iwsds2019.html#InoueHLNTK19

End-to-end Modeling for Selection of Utterance Constructional Units via System Internal States

Koki Tanaka, Koji Inoue, Shizuka Nakamura, Katsuya Takanashi, Tatsuya Kawahara

Lecture Notes in Electrical Engineering 714 15 - 27 2021年

掲載種別：論文集(書籍)内論文出版者・発行元：Springer

In order to make conversational agents or robots conduct human-like behaviors, it is important to design a model of the system internal states. In this paper, we address a model of favorable impression to the dialogue partner. The favorable impression is modeled to change according to user’s dialogue behaviors and also affect following dialogue behaviors of the system, specifically selection of utterance constructional units. For this modeling, we propose a hierarchical structure of logistic regression models. First, from the user’s dialogue behaviors, the model estimates the level of user’s favorable impression to the system and also the level of the user’s interest in the current topic. Then, based on the above results, the model predicts the system’s favorable impression to the user. Finally, the model determines selection of utterance constructional units in the next system turn. We train each of the logistic regression models individually with a small amount of annotated data of favorable impression. Afterward, the entire multi-layer network is fine-tuned with a larger amount of dialogue behavior data. An experimental result shows that the proposed method achieves higher accuracy on the selection of the utterance constructional units, compared with methods that do not take into account the system internal states.

DOI： 10.1007/978-981-15-9323-9_2

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その他リンク： https://dblp.uni-trier.de/db/conf/iwsds/iwsds2019.html#TanakaINTK19

Response Generation to Out-of-Database Questions for Example-Based Dialogue Systems

Sota Isonishi, Koji Inoue, Divesh Lala, Katsuya Takanashi, Tatsuya Kawahara

Lecture Notes in Electrical Engineering 704 303 - 317 2021年

掲載種別：研究論文（国際会議プロシーディングス）

Example-based dialogue systems are often used in practice because of their robustness and simple architecture. However, when these systems are given out-of-database questions that are not registered in the question-response database, they have to respond with a fixed backup response, which can make users disengaged in the dialogue. In this study, we address response generation for out-of-database questions to make users perceive that the system understands the question itself. We define question types observed in the speed-dating scenario which is based on open-domain dialogue. Then we define possible response frames for each question type. We propose a sequence-to-sequence model that directly generates an appropriate response frame from an input question sentence in an end-to-end manner. The proposed model also explicitly integrates a question type classification to take into account the question type of the out-of-database question. Experimental results show that integrating the question type classification improved the response generation, and could exactly match 69.2% of response frames provided by human annotators.

DOI： 10.1007/978-981-15-8395-7_23

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Engagement-Based Adaptive Behaviors for Laboratory Guide in Human-Robot Dialogue

Koji Inoue, Divesh Lala, Kenta Yamamoto, Katsuya Takanashi, Tatsuya Kawahara

Lecture Notes in Electrical Engineering 714 129 - 139 2021年

掲載種別：論文集(書籍)内論文出版者・発行元：Springer

We address an application of engagement recognition in human-robot dialogue. Engagement is defined as how much a user is interested in the current dialogue, and keeping users engaged is important for spoken dialogue systems. In this study, we apply a real-time engagement recognition model to laboratory guide by autonomous android ERICA which plays the role of the guide. According to an engagement score of a user, ERICA generates adaptive behaviors consisting of feedback utterances and additional explanations. A subject experiment showed that the adaptive behaviors increased both the engagement score and related subjective scores such as interest and empathy.

DOI： 10.1007/978-981-15-9323-9_11

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その他リンク： https://dblp.uni-trier.de/db/conf/iwsds/iwsds2019.html#InoueLYTK19

アンドロイドERICAの傾聴対話システムにおけるWOZとの比較評価

井上昂治, ララディベッシュ, 山本賢太, 中村静, 高梨克也, 河原達也

人工知能学会研究会資料 SLUD ( C002-21 ) 85 - 90 2020年11月

多様なふるまいからの好感判定に基づき発話構成要素を選択するお見合い対話システム

田中滉己, 井上昂治, 中村静, 高梨克也, 河原達也

人工知能学会研究会資料 SLUD ( C002-28 ) 129 - 134 2020年11月

Job interviewer android with elaborate follow-up question generation 査読国際誌

Koji Inoue, Kohei Hara, Divesh Lala, Kenta Yamamoto, Shizuka Nakamura, Katsuya Takanashi, Tatsuya Kawahara

ICMI2020 324 - 332 2020年10月

Job Interviewer Android with Elaborate Follow-up Question Generation

Koji Inoue, Kohei Hara, Divesh Lala, Kenta Yamamoto, Shizuka Nakamura, Katsuya Takanashi, Tatsuya Kawahara

ICMI 2020 - Proceedings of the 2020 International Conference on Multimodal Interaction 324 - 332 2020年10月

掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：ACM

A job interview is a domain that takes advantage of an android robot's human-like appearance and behaviors. In this work, our goal is to implement a system in which an android plays the role of an interviewer so that users may practice for a real job interview. Our proposed system generates elaborate follow-up questions based on responses from the interviewee. We conducted an interactive experiment to compare the proposed system against a baseline system that asked only fixed-form questions. We found that this system was significantly better than the baseline system with respect to the impression of the interview and the quality of the questions, and that the presence of the android interviewer was enhanced by the follow-up questions. We also found a similar result when using a virtual agent interviewer, except that presence was not enhanced.

DOI： 10.1145/3382507.3418839

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その他リンク： https://dblp.uni-trier.de/db/conf/icmi/icmi2020.html#InoueHLYNTK20

A character expression model affecting spoken dialogue behaviors 査読国際誌

Kenta Yamamoto, Koji Inoue, Shizuka Nakamura, Katsuya Takanashi, Tatsuya Kawahara

Internatinal Workshop for Spoken Dialogue Systems (IWSDS2020) 2020年9月

Response generation to out-of-database questions for example-based dialogue systems 査読国際誌

Sota Isonishi, Koji Inoue, Divesh Lala, Katsuya Takanashi, Tatsuya Kawahara

Internatinal Workshop for Spoken Dialogue Systems (IWSDS2020) 2020年9月

掘り下げ質問を行う就職面接対話システムの自律型アンドロイドでの実装と評価査読

井上昂治, 原康平, ララディベッシュ, 山本賢太, 中村静, 高梨克也, 河原達也

人工知能学会論文誌 35 ( 5 ) D - K43_1 2020年9月

An attentive listening system with android ERICA: Comparison of autonomous and WOZ Interactions 査読国際誌

Koji Inoue, Divesh Lala, Kenta Yamamoto, Shizuka Nakamura, Katsuya Takanashi, Tatsuya Kawahara

SIGdial 2020 Conference 118 - 127 2020年7月

自律型アンドロイドERICAによる就職面接対話

井上昂治, 原康平, LALA Divesh, 山本賢太, 中村静, 高梨克也, 河原達也

日本音響学会研究発表会講演論文集(CD-ROM) 2020 2020年

An Attentive Listening System with Android ERICA: Comparison of Autonomous and WOZ Interactions.

Koji Inoue, Divesh Lala, Kenta Yamamoto, Shizuka Nakamura, Katsuya Takanashi, Tatsuya Kawahara

Proceedings of the 21th Annual Meeting of the Special Interest Group on Discourse and Dialogue(SIGdial) 118 - 127 2020年

Dialogue Behavior Control Model for Expressing a Character of Humanoid Robots

Kenta Yamamoto, Koji Inoue, Shizuka Nakamura, Katsuya Takanashi, Tatsuya Kawahara

2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings 1732 - 1737 2019年3月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：IEEE

This paper addresses character expression for humanoid robots that play a social role via spoken dialogue so that the character matches to the given social role such as a lab guide or a counselor. While conventional methods of character expression mostly focused on changing the style of utterance texts, this study focuses on dialogue behavior features that may affect the impression of spoken dialogue. Specifically, we use five dialogue behavior features: utterance amount, backchannel frequency, backchannel variety, filler frequency, and switching pause length (the time until the system responds). We adopt three character traits of extroversion, emotional instability, and politeness for character expression. We then investigate the relationship between the dialogue behavior features and the character traits by conducting subjective evaluations. A statistical analysis of the subjective evaluations shows that the dialogue behavior features except for the backchannel variety are related to either of the character traits. By using the subjective evaluation scores on the relevant traits, we can train models to control the dialogue behavior features of a robot according to the desired character. Another experimental evaluation demonstrates the feasibility of character expression with regard to the traits of extroversion and politeness.

DOI： 10.23919/APSIPA.2018.8659624

Web of Science

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その他リンク： https://dblp.uni-trier.de/db/conf/apsipa/apsipa2018.html#YamamotoINTK18

移行適格場の予測に基づくターンテイキング予測

原康平, 井上昂治, 高梨克也, 河原達也

第81回全国大会講演論文集 2019 ( 1 ) 357 - 358 2019年2月

記述言語：日本語

音声対話システムが円滑な対話を実現するためには，次に話者が交替するか否か（ターンテイキング）の予測が重要である．本研究では，ターンテイキングの予測において，移行適格場（TRP）の情報を考慮する．TRPとは，話者交替が起こりうる箇所を指し，ターンテイキングのふるまいは，TRPか否かに依存すると考えらえる． TRPは客観的に定義できるため，予測が比較的容易である．提案モデルは，ニューラルネットに基づく二段階の予測を行う．はじめに，TRPの予測を行う．次に，TRP予測の結果を用いてターンテイキングの予測を行う．評価実験により，TRPの情報を用いることで，ターンテイキングの予測精度が向上することを確認した．

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質問タイプの分類に基づく用例なし質問に対する応答生成

磯西爽太, 田中滉己, 井上昂治, 高梨克也, 河原達也

第81回全国大会講演論文集 2019 ( 1 ) 359 - 360 2019年2月

記述言語：日本語

対話システムが人間らしい対話を実現するためには，システム自身の趣味や嗜好といったプロファイル情報を設定することが有効といえる．プロファイルの一貫性を保つためには，想定質問とその応答の用例を用意しておく必要がある．しかし，用例がない質問がなされた場合，従来のシステムでは「お答えできません」などの画一的な応答を返してしまう．そこで，これらの質問を「個人情報」，「好み」，「習慣」などのタイプに分類し，それぞれに対応した応答を生成する．これにより，その質問をシステムが理解しているかのようにみせかける．実験では，自律型アンドロイドERICAを用いたお見合い対話コーパスにおいて提案システムの有効性を検証する．

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対話のふるまい制御によるキャラクタ表現モデルと対話コーパスによる検証

山本賢太, 井上昂治, 中村静, 高梨克也, 河原達也

第81回全国大会講演論文集 2019 ( 1 ) 363 - 364 2019年2月

記述言語：日本語

我々は自律型アンドロイドERICAの研究開発を進めており，特定の社会的役割が与えられた状況での対話を扱っている．この際に，その社会的役割に適したキャラクタ（性格）をアンドロイドが表出することで，より自然な対話が実現できると考えらえる．これまでに，発話量，相槌，フィラー，交替潜時といった対話におけるシステムのふるまいを制御することで，外向性，情緒不安定性，丁寧さから成るキャラクタを表現するモデルを提案した．本稿では，遠隔操作されたアンドロイドとの対話コーパスを用いて，実際の対話のふるまいと知覚されるキャラクタとの関係が，提案モデルでも実現できることを検証した．

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