Recognition of intentions of users' short responses for conversational news delivery system

Hiroaki Takatsu, Katsuya Yokoyama, Yoichi Matsuyama, Hiroshi Honda, Shinya Fujie, Tetsunori Kobayashi

研究成果: Conference article査読

抄録

In human-human conversations, listeners often convey intentions to their speakers through feedbacks comprising reflexive short responses. The speakers then recognize these intentions and dynamically change the conversational plans to transmit information more efficiently. For the design of spoken dialogue systems that deliver a massive amount of information, such as news, it is essential to accurately capture users' intentions from reflexive short responses to efficiently select or eliminate the information to be transmitted depending on the user's needs. However, such short responses from users are normally too short to recognize their actual intentions only from the prosodic and linguistic features of their short responses. In this paper, we propose a user's short-response intention-recognition model that accounts for the previous system's utterances as the context of the conversation in addition to prosodic and linguistic features of user's utterances. To achieve this, we define types of short response intentions in terms of effective information transmission and created new dataset by annotating over the interaction data collected using our spoken dialogue system. Our experimental results demonstrate that the classification accuracy can be improved using the linguistic features of the system's previous utterances encoded by Bidirectional Encoder Representations from Transformers (BERT) as the conversational context.

本文言語English
ページ(範囲)1193-1197
ページ数5
ジャーナルProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
2019-September
DOI
出版ステータスPublished - 2019
イベント20th Annual Conference of the International Speech Communication Association: Crossroads of Speech and Language, INTERSPEECH 2019 - Graz, Austria
継続期間: 2019 9 152019 9 19

ASJC Scopus subject areas

  • 言語および言語学
  • 人間とコンピュータの相互作用
  • 信号処理
  • ソフトウェア
  • モデリングとシミュレーション

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