作者
Ananth Sankar, Chin-Hui Lee
发表日期
1996/5
期刊
IEEE transactions on speech and Audio Processing
卷号
4
期号
3
页码范围
190-202
出版商
IEEE
简介
Presents a maximum-likelihood (ML) stochastic matching approach to decrease the acoustic mismatch between a test utterance and a given set of speech models so as to reduce the recognition performance degradation caused by distortions in the test utterance and/or the model set. We assume that the speech signal is modeled by a set of subword hidden Markov models (HMM) /spl Lambda//sub x/. The mismatch between the observed test utterance Y and the models /spl Lambda//sub x/ can be reduced in two ways: 1) by an inverse distortion function F/sub /spl nu//(.) that maps Y into an utterance X that matches better with the models /spl Lambda//sub x/ and 2) by a model transformation function G/sub /spl eta//(.) that maps /spl Lambda//sub x/ to the transformed model /spl Lambda//sub x/ that matches better with the utterance Y. We assume the functional form of the transformations F/sub /spl nu//(.) or G/sub /spl eta …
引用总数
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A Sankar, CH Lee - IEEE transactions on speech and Audio Processing, 1996