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HMM-based strategies for enhancement of speech signals embedded in nonstationary noise

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4 Author(s)
Sameti, H. ; Dept. of Electr. & Comput. Eng., Waterloo Univ., Ont., Canada ; Sheikhzadeh, H. ; Li Deng ; Brennan, R.L.

An improved hidden Markov model-based (HMM-based) speech enhancement system designed using the minimum mean square error principle is implemented and compared with a conventional spectral subtraction system. The improvements to the system are: (1) incorporation of mixture components in the HMM for noise in order to handle noise nonstationarity in a more flexible manner, (2) two efficient methods in the speech enhancement system design that make the system real-time implementable, and (3) an adaptation method to the noise type in order to accommodate a wide variety of noise expected under the enhancement system's operating environment. The results of the experiments designed to evaluate the performance of the HMM-based speech enhancement systems in comparison with spectral subtraction are reported. Three types of noise-white noise, simulated helicopter noise, and multitalker (cocktail party) noise-were used to corrupt the test speech signals. Both objective (global SNR) and subjective mean opinion score (MOS) evaluations demonstrate consistent superiority of the HMM-based enhancement systems that incorporate the innovations described in this paper over the conventional spectral subtraction method

Published in:

Speech and Audio Processing, IEEE Transactions on  (Volume:6 ,  Issue: 5 )

Date of Publication:

Sep 1998

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