Abstract
Speech recognition in a noisy environment is one of the hottest topics in the speech recognition research. Noise-tolerant acoustic models or noise reduction techniques are often used to improve recognition accuracy. In this paper, we propose a method to improve accuracy of spoken dialog system from a language model point of view. In the proposed method, the dialog system automatically changes its language model and dialog strategy according to the estimated recognition accuracy in a noisy environment in order to keep the performance of the system high. In a noise-free environment, the system accepts any utterance from a user. On the other hand, the system restricts its grammar and vocabulary in a noisy environment. To realize this strategy, we investigated a method to avoid the user's out-of-grammar utterances through an instruction given by the system to a user. Furthermore, we developed a method to estimate recognition accuracy from features extracted from noise signals. Finally, we realized a proposed dialog system according to these investigations.
Original language | English |
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Pages (from-to) | 538-548 |
Number of pages | 11 |
Journal | IEICE Transactions on Information and Systems |
Volume | E91-D |
Issue number | 3 |
DOIs | |
Publication status | Published - 2008 Mar |
Keywords
- Dialog strategy
- Neural network
- Noisy environment
- Speech recognition
- Spoken dialog system
ASJC Scopus subject areas
- Software
- Hardware and Architecture
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering
- Artificial Intelligence