Title of Paper:Single Channel Source Separation Using EMD-Subband Variable Regularized Sparse Features

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Journal:IEEE Transactions on Audio, Speech and Language Processing

Abstract:A novel approach to solve the single channel source separation (SCSS) problem is presented. Most existing supervised SCSS methods resort exclusively to the independence waveform criteria as exemplified by training the prior information before the separation process. This poses a significant limiting factor to the applicability of these methods to real problem. Our proposed method does not require training knowledge for separating the mixture and it is based on decomposing the mixture into a series of oscillatory components termed as the intrinsic mode functions (IMF).

All the Authors: S.S. Dlay, W.L. Woo,Bin Gao

Correspondence Author:Bin Gao

Discipline:Engineering

Volume:19

Issue:4

Page Number:961-976

Translation or Not:no

Date of Publication:2011-03-30