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Noise compensation methods for hidden Markov model speech recognition in adverse environments

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2 Author(s)
Vaseghi, S.V. ; Dept. of Electr. & Electron. Eng., Queen''s Univ., Belfast, UK ; Milner, B.P.

Several noise compensation schemes for speech recognition in impulsive and nonimpulsive noise are considered. The noise compensation schemes are spectral subtraction, HMM-based Wiener (1949) filters, noise-adaptive HMMs, and a front-end impulsive noise removal. The use of the cepstral-time matrix as an improved speech feature set is explored, and the noise compensation methods are extended for use with cepstral-time features. Experimental evaluations, on a spoken digit database, in the presence of ear noise, helicopter noise, and impulsive noise, demonstrate that the noise compensation methods achieve substantial improvement in recognition across a wide range of signal-to-noise ratios. The results also show that the cepstral-time matrix is more robust than a vector of identical size, which is composed of a combination of cepstral and differential cepstral features

Published in:

Speech and Audio Processing, IEEE Transactions on  (Volume:5 ,  Issue: 1 )

Date of Publication:

Jan 1997

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