Automatic Speech Recognition and UnderstandingIEEE, 2003 - Automatic speech recognition |
Contents
Trends in | 1 |
Speaker Specific Processing | 19 |
Speech Recognition LVCSR | 37 |
Copyright | |
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accented acoustic model adaptation algorithm applied approach ASR system automatic speech recognition barge-in baseline bigram cepstral cepstrum classification clean speech clustering coefficients components computed confidence measure confidence scoring context corpus database decision tree decoding detection dialogue system domain estimated evaluation experiments extraction feature vector Figure filled pauses filtering frame frequency function Gaussian grammar hidden Markov models HLDA ICASSP IEEE improvement initial input iteration labels language model lattice likelihood linear mapping maximum likelihood method MFCC MLLR N-best n-gram node noise obtained optimal output paper parameters parsing performance phoneme pitch posterior probability probability Proc pronunciation proposed prosody recognition results recognizer reduced robust segmentation selection semantic sentence sequence shows speaker spectral speech signal spoken syllable Table task techniques test set tion training data training set transcription transform trigram utterances values variable vocabulary word accuracy word error rate