Abstract
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 language | English |
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Pages (from-to) | 3359-3367 |
Number of pages | 9 |
Journal | IEICE Transactions on Information and Systems |
Volume | E93-D |
Issue number | 12 |
DOIs | |
Publication status | Published - 2010 Dec |
Externally published | Yes |
Keywords
- 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