Proceedings of 1994 28th Asilomar Conference on Signals, Systems and Computers (1994)
Pacific Grove, CA, USA
Oct. 31, 1994 to Nov. 2, 1994
M.E. Deisher , Dept. of Electr. Eng., Arizona State Univ., Tempe, AZ, USA
A.S. Spanias , Dept. of Electr. Eng., Arizona State Univ., Tempe, AZ, USA
An analysis/synthesis technique based on harmonic sinusoidal modeling of speech is used to develop a new hidden Markov model (HMM) based speech enhancement algorithm. State sequence estimation is done using a standard HMM-based approach. State-based enhancement is carried out by assuming a harmonic model for speech, i.e., by representing each block of speech as a sum of sine waves in terms of a set of amplitudes, phases, and harmonically related frequencies. Given the maximum a-posteriori probability (MAP) state sequence, the amplitudes, phases, voicing, and fundamental frequency are estimated. Simulation results are presented, comparing the performance of the proposed algorithm to that of a standard HMM-based approach. The proposed method was found to reduce the structured residual noise normally associated with HMM-based algorithms.<
speech enhancement, hidden Markov models, transforms, estimation theory, harmonic analysis, maximum likelihood estimation, speech intelligibility, noise abatement, acoustic noise, land mobile radio
M. Deisher and A. Spanias, "Speech enhancement using a state-based transform model," Proceedings of 1994 28th Asilomar Conference on Signals, Systems and Computers(ACSSC), Pacific Grove, CA, USA, 1995, pp. 1242-1246.