Blind Source Separation Combining Simo-Ica and Simo-Model-Based Binary Masking

A new two-stage blind source separation (BSS) for convolutive mixtures of speech is proposed, in which a single-input multiple-output (SIMO)-model-based ICA and a new SIMO-model-based binary mask processing are combined. SIMO-model-based ICA can separate the mixed signals, not into monaural source s...

Full description

Saved in:
Bibliographic Details
Published in2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings Vol. 5; p. V
Main Authors Mori, Y., Takatani, T., Saruwatari, H., Hiekata, T., Morita, T.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2006
Subjects
Blind source separation
Discrete Fourier transforms
Filters
Frequency domain analysis
Independent component analysis
Interference
Microphone arrays
Source separation
Speech coding
Speech processing
Online AccessGet full text

Cover

More Information
Summary:A new two-stage blind source separation (BSS) for convolutive mixtures of speech is proposed, in which a single-input multiple-output (SIMO)-model-based ICA and a new SIMO-model-based binary mask processing are combined. SIMO-model-based ICA can separate the mixed signals, not into monaural source signals but into SIMO-model-based signals from independent sources as they are at the microphones. Thus, the separated signals of SIMO-model-based ICA can maintain the spatial qualities of each sound source. Owing to the attractive property, novel SIMO-model-based binary mask processing can be applied to efficiently remove the residual interference components after SIMO-model-based ICA. The experimental results reveal that the separation performance can be considerably improved by using the proposed method compared with the conventional BSS methods
ISBN:9781424404698
142440469X
ISSN:1520-6149
2379-190X
DOI:10.1109/ICASSP.2006.1661217