Maximum likelihood approach for blind audio source separation using time-frequency Gaussian source models

Author

Févotte, Cédric ; Cardoso, Jean-François

Author_Institution

Dept. of Eng., Cambridge Univ., UK

fYear

2005

fDate

16-19 Oct. 2005

Firstpage

78

Lastpage

81

Abstract

In this paper we propose a simple time-frequency Gaussian model of audio signals that allows for separation of possibly underdetermined and noisy linear instantaneous mixtures. An efficient EM algorithm is proposed to estimate the mixing matrix, the noise covariance and covariances of the source t-f coefficients over a chosen frame/subband tiling of the time-frequency domain. Results are given on 4 × 4 and 3 × 4 noisy mixtures of audio sources.

Keywords

Gaussian noise; audio signal processing; blind source separation; maximum likelihood estimation; time-frequency analysis; EM algorithm; audio signals; blind audio source separation; maximum likelihood approach; noise covariance; noisy mixtures; time-frequency Gaussian source models; Blind source separation; Covariance matrix; Gaussian noise; Higher order statistics; Maximum likelihood estimation; Noise level; Signal processing; Signal processing algorithms; Source separation; Time frequency analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Applications of Signal Processing to Audio and Acoustics, 2005. IEEE Workshop on

Print_ISBN

0-7803-9154-3

Type

conf

DOI

10.1109/ASPAA.2005.1540173

Filename

1540173