Title :
Frequency bin nonlinear LMS adaptive noise canceler and its application to co-channel speech noise reduction
Author :
Gu, Yu Hua ; Van Bokhoven, W. M G
Author_Institution :
Dept. of Electr. Eng., Eindhoven Univ. of Technol., Netherlands
Abstract :
The transform domain normalized least mean square (LMS) linear filtering algorithm is extended to the nonlinear (NL) case under Gaussian filter input assumption. Properties of the transform domain NL algorithms are also investigated. By choosing a proper orthogonal transform, a faster convergence speed and a significant reduction of the numbers of NL filter weights can be obtained. A promising application is proposed to cochannel speech noise reduction. Promising results of speech intelligibility enhancement are obtained over a range of SNR between 0 dB and ±12 dB. Spectrograms and informal listening tests of the enhanced target speech provide evidence of the proposed approach
Keywords :
adaptive filters; convergence; filtering and prediction theory; interference suppression; least squares approximations; signal processing; speech analysis and processing; speech intelligibility; -12 to 12 dB; Gaussian filter input assumption; LMS adaptive noise canceler; cochannel speech noise reduction; convergence speed; frequency bin; least mean square; nonlinear filter weights; orthogonal transform; speech intelligibility enhancement; transform domain normalized; Convergence; Filtering algorithms; Frequency; Least squares approximation; Maximum likelihood detection; Noise cancellation; Noise reduction; Nonlinear filters; Signal to noise ratio; Speech enhancement;
Conference_Titel :
Circuits and Systems, 1991., IEEE International Sympoisum on
Print_ISBN :
0-7803-0050-5
DOI :
10.1109/ISCAS.1991.176131
