Title :
Sequential noise estimation for noise-robust speech recognition based on 1st-order VTS approximation
Author :
Ding, Guo-Hong ; Wang, Xia ; Cao, Yang ; Ding, Feng ; Tang, Yuezhong
Author_Institution :
Nokia Res. Center, Beijing
Abstract :
In this paper, a novel sequential noise estimation algorithm is proposed based on the 1st-order vector Taylor series (VTS) approximation to the nonlinear environmental function. The estimation formulas are derived in the sequential expectation-maximum (EM) criterion. Noise parameters, both the mean vectors and the covariance matrices, are estimated frame by frame directly with the aim to maximize the objective function. Experimental results demonstrate the great advantage of the proposed sequential noise estimation algorithm over the alternatives in the 1st-order VTS based feature compensation framework and show that the performance improvement comes partly from the involvement of noise covariance in the 1st-order VTS based noise compensation and partly from the introduction of noise covariance in the sequential noise estimation
Keywords :
covariance matrices; expectation-maximisation algorithm; sequential estimation; series (mathematics); speech recognition; covariance matrices; noise-robust speech recognition; sequential expectation-maximum criterion; sequential noise estimation; vector Taylor series approximation; Additive noise; Approximation algorithms; Covariance matrix; Noise robustness; Recursive estimation; Speech enhancement; Speech recognition; Stochastic resonance; Taylor series; Working environment noise;
Conference_Titel :
Automatic Speech Recognition and Understanding, 2005 IEEE Workshop on
Conference_Location :
San Juan
Print_ISBN :
0-7803-9478-X
Electronic_ISBN :
0-7803-9479-8
DOI :
10.1109/ASRU.2005.1566526
