Title :
Weight-Space Viterbi Decoding Based Spectral Subtraction for Reverberant Speech Recognition
Author :
Sung Min Ban ; Hyung Soon Kim
Author_Institution :
Dept. of Electron. Eng., Pusan Nat. Univ., Busan, South Korea
Abstract :
A single-channel blind dereverberation algorithm is proposed in this letter for distant-talking speech recognition. The proposed method is based on spectral subtraction (SS) method, in which the spectrum of a late reverberant signal is estimated using a delayed and attenuated version of the reverberant signal. Through some assumptions, the conventional SS method regards the attenuation weight as a constant that is a function of reverberation time. However, these assumptions are not valid in real situations, and the ideal weight varies with the frame. Therefore, in the proposed method, the variable weight sequence is estimated using Viterbi decoding scheme based on the reverberation model. This weight sequence is then substituted for the fixed weight in the conventional SS method without explicitly estimating the reverberation time. The proposed method performs better than the conventional SS method in both isolated word recognition and connected digit recognition experiments in reverberant environments.
Keywords :
Viterbi decoding; reverberation; sequential estimation; spectral analysis; speech coding; speech recognition; attenuation weight; connected digit recognition; conventional SS method; distant talking speech recognition; isolated word recognition; late reverberant signal spectrum estimation; reverberant environments; reverberation model; single channel blind dereverberation algorithm; spectral subtraction method; variable weight sequence estimation; weight-space Viterbi decoding; Decoding; Hidden Markov models; Reverberation; Speech; Speech recognition; Vectors; Viterbi algorithm; Dereverberation; spectral subtraction; speech recognition; viterbi decoding;
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2015.2408371