Selecting Help Messages by Using Robust Grammar Verification for Handling Out-of-Grammar Utterances in Spoken Dialogue Systems

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...

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Published inIEICE transactions on information and systems Vol. E93.D; no. 12; pp. 3359 - 3367
Main Authors Komatani, Kazunori, Fukubayashi, Yuichiro, Ikeda, Satoshi, Ogata, Tetsuya, Okuno, Hiroshi G
Format Journal Article
LanguageJapanese
Published 01.01.2010
Subjects
Algorithms
Automatic speech recognition
Grammars
Handling
Materials handling
Messages
Ranking
Transducers
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Summary: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.
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ISSN:1745-1361
DOI:10.1587/transinf.E93.D.3359