Selecting help messages by using robust grammar verification for handling out-of-grammar utterances in spoken dialogue systems

Kazunori Komatani, Yuichiro Fukubayashi, Satoshi Ikeda, Tetsuya Ogata, Hiroshi G. Okuno

Research output: Contribution to journalArticle

1 Citation (Scopus)


We address the issue of out-of-grammar (OOG) utterances in spoken dialogue systems by generating help messages. Help message generation for OOG utterances is a challenge because language understanding based on automatic speech recognition (ASR) of OOG utterances is usually erroneous; important words are often misrecognized or missing from such utterances. Our grammar verification method uses a weighted finite-state transducer, to accurately identify the grammar rule that the user intended to use for the utterance, even if important words are missing from the ASR results. We then use a ranking algorithm, RankBoost, to rank help message candidates in order of likely usefulness. Its features include the grammar verification results and the utterance history representing the user's experience.

Original languageEnglish
Pages (from-to)3359-3367
Number of pages9
JournalIEICE Transactions on Information and Systems
Issue number12
Publication statusPublished - 2010 Dec



  • Help generation
  • Novice user
  • Out-of-grammar utterances
  • Spoken dialogue system
  • Utterance history

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence

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