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Enhancement and recognition of noisy speech within an autoregressive hidden Markov model framework using noise estimates from the noisy signal

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2 Author(s)
B. T. Logan ; Dept. of Eng., Cambridge Univ., UK ; A. J. Robinson

This paper describes a new algorithm to enhance and recognise noisy speech when only the noisy signal is available. The system uses autoregressive hidden Markov models (HMMs) to model the clean speech and noise and combines these to form a model for the noisy speech. The probability framework developed is then used to reestimate the noise models from the corrupted speech waveform and the process is repeated. Enhancement is performed using the Wiener filters formed from the final clean speech models and noise estimates. Results are presented for additive stationary Gaussian and coloured noise

Published in:

Acoustics, Speech, and Signal Processing, 1997. ICASSP-97., 1997 IEEE International Conference on  (Volume:2 )

Date of Conference:

21-24 Apr 1997