Referenced Items are not available for this document.
Linear channel compensation in speech recognition typically involves estimating an additive shift in the cepstral domain. This paper explores both Bayesian and maximum likelihood techniques to transform either the features or the model parameters. Experiments on the Macrophone corpus show error rate reductions of up to 16% over cepstral mean subtraction for short utterances
Published in:
Speech and Audio Processing, IEEE Transactions on
(Volume:7
,
Issue:
5
)
Date of Publication: Sep 1999
- Page(s):
- 594 - 597
- ISSN :
- 1063-6676
- INSPEC Accession Number:
- 6357465
- Digital Object Identifier :
- 10.1109/89.784112
- Product Type:
- Journals & Magazines
- Date of Current Version :
- 06 August 2002
- Issue Date :
- Sep 1999
- Sponsored by :
- IEEE Signal Processing Society
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