An Improved Speech Blind Separation Algorithm Based on Non-Linear Function

Zhu Cheng Li

doi:10.4028/www.scientific.net/AMM.239-240.1264

Paper Titles

The Output Model of FOG North-Finding System Constructed by the ARMA Timing Analysis
p.1246

A Novel GVF-Based Adaptive Extracting Formulation for Image Reconstruction
p.1250

A Simplified Carrier Frequency Offset Estimation Algorithm for Burst Digital Transmission
p.1255

The Characteristic Parameters Extraction of the Drawing Forming Cracks Based on Time-Series Analysis and ICA
p.1259

An Improved Speech Blind Separation Algorithm Based on Non-Linear Function
p.1264

Applications of Statistical Directional Characteristics in Synthetic Aperture Radar Imagery Interpretation
p.1269

Research on the Speech Enhancement Method based on PCA/KLT Algorithms
p.1274

Bridging a Gap in Independent Component Analysis
p.1279

A QRS Wave Detection Algorithm Based on Complex Wavelet Transform
p.1284

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 239-240An Improved Speech Blind Separation Algorithm...

An Improved Speech Blind Separation Algorithm Based on Non-Linear Function

Abstract:

This paper introduces a new algorithm based on non-linear function to adaptively control step-size which is used for updating separation matrix to extract a target speech source accurately in blind source separation (BSS). The use of fixed step-size parameter of the conventional BSS algorithm usually results in a trade-off between convergence speed and steady-state misadjustment. The presented algorithm will eliminate much of this trade-off. It intelligently regulates the step-size according to the time-varying dynamics of other parameters at each iteration. The desirable ability of the new algorithm to improve convergence speed and steady-state misadjustment is demonstrated by MATLAB simulation results.