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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

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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.

Publication
IEICE TRANSACTIONS on Information Vol.E93-D No.12 pp.3359-3367
Publication Date
2010/12/01
Publicized
Online ISSN
1745-1361
DOI
10.1587/transinf.E93.D.3359
Type of Manuscript
PAPER
Category
Speech and Hearing

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