Underdetermined sparse source separation of convolutive mixtures with observation vector clustering

Shoko Arakiti*, Hiroshi Sawada, Ryo Mukai, Shoji Makino

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

We propose a new method for solving the underdetermined sparse signal separation problem. Some sparseness based methods have already been proposed. However, most of these methods utilized a linear sensor array (or only two sensors), and therefore they have certain limitations; e.g., they cannot separate symmetrically positioned sources. To allow the use of more than three sensors that can be arranged in a non-linear/non-uniform way, we propose a new method that includes the normalization and clustering of the observation vectors. Our proposed method can handle both underdetermined case and (over-)determined cases. We show practical results for speech separation with nonlinear/non-uniform sensor arrangements. We obtained promising experimental results for the cases of 3 × 4, 4 × 5 (#sensors × #sources) in a room (RT60 = 120 ms).

Original languageEnglish
Title of host publicationISCAS 2006
Subtitle of host publication2006 IEEE International Symposium on Circuits and Systems, Proceedings
Pages3594-3597
Number of pages4
Publication statusPublished - 2006
Externally publishedYes
EventISCAS 2006: 2006 IEEE International Symposium on Circuits and Systems - Kos, Greece
Duration: 2006 May 212006 May 24

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
ISSN (Print)0271-4310

Conference

ConferenceISCAS 2006: 2006 IEEE International Symposium on Circuits and Systems
Country/TerritoryGreece
CityKos
Period06/5/2106/5/24

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Underdetermined sparse source separation of convolutive mixtures with observation vector clustering'. Together they form a unique fingerprint.

Cite this