Online error detection of barge-in utterances by using individual users' utterance histories in spoken dialogue system

Kazunori Komatani*, Hiroshi G. Okuno

*この研究の対応する著者

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

We develop a method to detect erroneous interpretation results of user utterances by exploiting utterance histories of individual users in spoken dialogue systems that were deployed for the general public and repeatedly utilized. More specifically, we classify barge-in utterances into correctly and erroneously interpreted ones by using features of individual users' utterance histories such as their barge-in rates and estimated automatic speech recognition (ASR) accuracies. Online detection is enabled by making these features obtainable without any manual annotation or labeling. We experimentally compare classification accuracies for several cases when an ASR confidence measure is used alone or in combination with the features based on the user's utterance history. The error reduction rate was 15% when the utterance history was used.

本文言語English
ホスト出版物のタイトルProceedings of the SIGDIAL 2010 Conference: 11th Annual Meeting of the Special Interest Group onDiscourse and Dialogue
ページ289-296
ページ数8
出版ステータスPublished - 2010
外部発表はい
イベント11th Annual Meeting of the Special Interest Group on Discourse and Dialogue, SIGDIAL 2010 - Tokyo
継続期間: 2010 9 242010 9 25

Other

Other11th Annual Meeting of the Special Interest Group on Discourse and Dialogue, SIGDIAL 2010
CityTokyo
Period10/9/2410/9/25

ASJC Scopus subject areas

  • コンピュータ グラフィックスおよびコンピュータ支援設計
  • コンピュータ ビジョンおよびパターン認識
  • 人間とコンピュータの相互作用
  • モデリングとシミュレーション

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