Speech source separation in convolutive environments using space-time-frequency analysis
type: Item
instance of: scholarly article
title: Speech source separation in convolutive environments using space-time-frequency analysis
zbMATH Open document ID: 1122.94309
DOI: 10.1155/ASP/2006/38412
author: Shlomo Dubnov
author: Joseph Tabrikian
author: Miki Arnon-Targan
published in: EURASIP Journal on Applied Signal Processing
publication date: 2007-03-19T00:00:00Z
review text: Summary: We propose a new method for speech source separation that is based on directionally-disjoint estimation of the transfer functions between microphones and sources at different frequencies and at multiple times. The spatial transfer functions are estimated from eigenvectors of the microphones' correlation matrix. Smoothing and association of transfer function parameters across different frequencies are performed by simultaneous extended Kalman filtering of the amplitude and phase estimates. This approach allows transfer function estimation even if the number of sources is greater than the number of microphones, and it can operate for both wideband and narrowband sources. The performance of the proposed method was studied via simulations and the results show good performance.
Mathematics Subject Classification ID: 94A12
zbMATH DE Number: 5134692
Wikidata QID: Q59212442
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/asp/2006/38412
OpenAlex ID: W2087288261
DBLP publication ID: journals/ejasp/DubnovTA06
description: scientific article; zbMATH DE number 5134692