Title :
Subband-based adaptive decorrelation filtering for co-channel speech separation
Author :
Huang, Jonathan ; Yen, Kuan-Chieh ; Zhao, Yunxin
Author_Institution :
Latitude Commun., Santa Clara, CA, USA
fDate :
7/1/2000 12:00:00 AM
Abstract :
A subband-based adaptive decorrelation filtering algorithm (SBADF) is proposed for co-channel speech separation. The SBADF decomposes the input signals into several frequency subbands, and uses the adaptive decorrelation filtering algorithm (ADF) to process the signals in each subband independently. The processed subband signals are then combined for each channel to form the separated speech. Experimental results show that while the fullband ADF can achieve better separation performance after reaching convergence, the SBADF has the advantage of improved convergence rate and reduced computational complexity by a factor of approximately two
Keywords :
adaptive filters; adaptive signal processing; computational complexity; convergence of numerical methods; decorrelation; filtering theory; speech processing; adaptive decorrelation filtering algorithm; co-channel speech separation; convergence rate; experimental results; filtering algorithm; frequency subbands; fullband ADF; input signals decomposition; reduced computational complexity; separation performance; signal to interference ratio; subband signals processing; subband-based adaptive decorrelation filtering; Adaptive filters; Computational complexity; Convergence; Decorrelation; Filtering algorithms; Finite impulse response filter; Least squares approximation; Microphones; Signal processing; Speech processing;
Journal_Title :
Speech and Audio Processing, IEEE Transactions on