Please use this identifier to cite or link to this item: http://hdl.handle.net/1783.1/2438

A multi-path syllable to word decoder with language model optimization and automatic lexicon augmentation

Authors Tang, Haijiang
Fung, Pascale N.
Issue Date 2000
Source Proceedings 6th International Conference of Spoken Language Processing (Interspeech 2000), Beijing, China, 16-20 October 2000
Summary Syllable to word decoding plays a very important role in Chinese large vocabulary continuous speech recognition (LVCSR). However, lack of word boundary and other characteristics of Chinese language prohibits the development of high quality language model decoder. In this paper, we present a multi-path search with language model optimization and automatic lexicon augmentation method to improve the accuracy of syllable to word decoding. The experiment result shows that our method achieves 34.76% character accuracy improvment over baseline performance.
Subjects
Rights We would like to give credit to International Speech Communication Association for granting us permission to repost this article.
Language English
Format Conference paper
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