Bayesian learning of confidence measure function for generation of utterances and motions in object manipulation dialogue task

Komei Sugiura, Naoto Iwahashi, Hideki Kashioka, Satoshi Nakamura

研究成果: Conference article査読

8 被引用数 (Scopus)

抄録

This paper proposes a method that generates motions and utterances in an object manipulation dialogue task. The proposed method integrates belief modules for speech, vision, and motions into a probabilistic framework so that a user's utterances can be understood based on multimodal information. Responses to the utterances are optimized based on an integrated confidence measure function for the integrated belief modules. Bayesian logistic regression is used for the learning of the confidence measure function. The experimental results revealed that the proposed method reduced the failure rate from 12% down to 2.6% while the rejection rate was less than 24%.

本文言語English
ページ(範囲)2483-2486
ページ数4
ジャーナルProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
出版ステータスPublished - 2009 11 26
外部発表はい
イベント10th Annual Conference of the International Speech Communication Association, INTERSPEECH 2009 - Brighton, United Kingdom
継続期間: 2009 9 62009 9 10

ASJC Scopus subject areas

  • 人間とコンピュータの相互作用
  • 信号処理
  • ソフトウェア
  • 感覚系

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