Title :
A new perceptual convolutive blind source separation algorithm for speech separation
Author :
Pan, Qiongfeng ; Aboulnasr, Tyseer
Author_Institution :
Sch. of Information Technol. & Eng., Ottawa Univ., Ont., Canada
fDate :
31 Aug.-4 Sept. 2004
Abstract :
In this paper, we address the problem of blind speech signal separation. A new perceptual convolutive blind source separation algorithm is proposed based on filtered-E LMS algorithm and the masking properties of human auditory system. This algorithm emphasizes frequencies to which the human ear is sensitive and de-emphasizes frequencies that are inaudible to human ear by incorporating the properties of human auditory system making it suitable for speech separation. Simulation results on blind speech signal separation show that the proposed algorithm can improve the separated speech quality and has better convergence performance.
Keywords :
blind source separation; convolution; filtering theory; hearing; speech processing; filtered-E LMS algorithm; human auditory system; human ear; perceptual convolutive blind source separation algorithm; speech separation; Auditory system; Blind source separation; Ear; Frequency; Humans; Least squares approximation; Psychoacoustic models; Signal processing; Source separation; Speech;
Conference_Titel :
Signal Processing, 2004. Proceedings. ICSP '04. 2004 7th International Conference on
Print_ISBN :
0-7803-8406-7
DOI :
10.1109/ICOSP.2004.1452647