Abstract
Error correction techniques have been proposed in the applications of language learning and spoken dialogue systems for spoken language understanding. These techniques include two consecutive stages: the generation of correction candidates and the selection of correction candidates. In this study, a Context-Dependent Syllable Cluster (CD-SC)-based Confusion Matrix is proposed for the generation of correction candidates. A Contextual Fitness Score, measuring the sequential relationship to the neighbors of the candidate, is proposed for corrected syllable sequence selection. Finally, the n-gram language model is used to determine the final word sequence output. Experiments show that the proposed method improved from 0.742 to 0.771 in terms of BLEU score as compared to the conventional speech recognition mechanism.
Original language | English |
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Pages (from-to) | 1633-1636 |
Number of pages | 4 |
Journal | Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH |
Publication status | Published - 2011 |
Event | 12th Annual Conference of the International Speech Communication Association, INTERSPEECH 2011 - Florence, Italy Duration: 2011 Aug 27 → 2011 Aug 31 |
All Science Journal Classification (ASJC) codes
- Language and Linguistics
- Human-Computer Interaction
- Signal Processing
- Software
- Modelling and Simulation