DocumentCode :
1020823
Title :
Speaker adaptation via VQ prototype modification
Author :
Rtischev, D. ; Nahamoo, David ; Picheny, Michael
Author_Institution :
IBM Thomas J. Watson Res. Center, Yorktown Heights, NY, USA
Volume :
2
Issue :
1
fYear :
1994
Firstpage :
94
Lastpage :
97
Abstract :
A statistical technique for vector quantizer (VQ) prototype adaptation, based on tied-mixture continuous-parameter HMM´s, is derived and evaluated on the basis of experimental evidence. Performance on difficult adaptation tasks indicates that VQ-prototype adaptation via tied-mixture HMM´s constitutes a useful mechanism for speaker adaptation, particularly when there are substantial channel differences or when there is a large mismatch between reference and target speaker characteristics.
Keywords :
decoding; hidden Markov models; speech coding; speech recognition; vector quantisation; VQ prototype modification; decoder; hidden Markov model; recognition performance; speaker adaptation; speaker characteristics mismatch; speech recognition system; statistical technique; tied-mixture continuous-parameter HMM; vector quantizer; Clustering algorithms; Decoding; Hidden Markov models; Iterative algorithms; Labeling; Loudspeakers; Maximum likelihood estimation; Modems; Prototypes; Speech recognition;
fLanguage :
English
Journal_Title :
Speech and Audio Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1063-6676
Type :
jour
DOI :
10.1109/89.260340
Filename :
260340
Link To Document :
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