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Convention Paper

Speech Separation with Microphone Arrays Using the Mean Shift Algorithm

Authors: Ayllón, David; Gil-Pita, Roberto; Rosa-Zurera, Manuel

AES Convention 133 · Paper 8799 · October 2012

Abstract

Microphone arrays provide spatial resolution that is useful for speech source separation due to the fact that sources located in different positions cause different time and level differences in the elements of the array. This feature can be combined with time-frequency masking in order to separate speech mixtures by means of clustering techniques, such as the so-called DUET algorithm, which uses only two microphones. However, there are applications where larger arrays are available, and the separation can be performed using all these microphones. A speech separation algorithm based on mean shift clustering technique has been recently proposed using only two microphones. In this work the aforementioned algorithm is generalized for arrays of any number of microphones, testing its performance with echoic speech mixtures. The results obtained show that the generalized mean shift algorithm notably outperforms the results obtained by the original DUET algorithm.

Details

Published in
AES Convention 133
AES Convention
133
Paper number
8799
Publication date
October 6, 2012
Session subject
Analysis and Synthesis of Sound
Affiliation
University of Alcala, Alcalá de Henares, Spain (See document for exact affiliation information.)
Type
Convention Paper