Title :
Speech recognition and enhancement by a nonstationary AR HMM with gain adaptation under unknown noise
Author :
Ruske, Gunther ; Lee, Ki Yong
Author_Institution :
Inst. for Human-Machine-Commun., Munich Univ. of Technol., Germany
Abstract :
A gain-adapted speech recognition in unknown noise is developed in time domain. The noise is assumed to be the colored noise. The nonstationary autoregressive (NAR) hidden Markov model (HMM) used to model clean speeches. The nonstationary AR is modeled by polynomial functions with a linear combination of M known basis functions. Enhancement using multiple Kalman filters is performed for the gain contour of speech and estimation of noise model when only the noisy signal is available
Keywords :
Kalman filters; autoregressive processes; filtering theory; hidden Markov models; noise; polynomials; speech enhancement; speech recognition; time-domain analysis; basis functions; clean speech model; gain adaptation; gain contour; hidden Markov model; multiple Kalman filters; noise model; noisy signal; nonstationary AR HMM; nonstationary autoregressive HMM; polynomial functions; speech enhancement; speech recognition; unknown noise; Acoustic noise; Colored noise; Hidden Markov models; Liquids; Performance gain; Polynomials; Speech enhancement; Speech recognition; Stochastic resonance; Testing;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1999. Proceedings., 1999 IEEE International Conference on
Conference_Location :
Phoenix, AZ
Print_ISBN :
0-7803-5041-3
DOI :
10.1109/ICASSP.1999.758157
