Identification of Active Sources in Single-Channel Convolutive Mixtures Using Known Source Models

Sundar, Harshavardhan and Sreenivas, Thippur V and Kellermann, Walter (2013) Identification of Active Sources in Single-Channel Convolutive Mixtures Using Known Source Models. In: IEEE SIGNAL PROCESSING LETTERS, 20 (2).

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Abstract

We address the problem of identifying the constituent sources in a single-sensor mixture signal consisting of contributions from multiple simultaneously active sources. We propose a generic framework for mixture signal analysis based on a latent variable approach. The basic idea of the approach is to detect known sources represented as stochastic models, in a single-channel mixture signal without performing signal separation. A given mixture signal is modeled as a convex combination of known source models and the weights of the models are estimated using the mixture signal. We show experimentally that these weights indicate the presence/absence of the respective sources. The performance of the proposed approach is illustrated through mixture speech data in a reverberant enclosure. For the task of identifying the constituent speakers using data from a single microphone, the proposed approach is able to identify the dominant source with up to 8 simultaneously active background sources in a room with RT60 = 250 ms, using models obtained from clean speech data for a Source to Interference Ratio (SIR) greater than 2 dB.

Item Type:	Journal Article
Publication:	IEEE SIGNAL PROCESSING LETTERS
Publisher:	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Additional Information:	Copyright for this article belongs to IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC,USA
Keywords:	Latent variable approach;multiple source identification;single channel;Student's-t Mixture Models (tMMs)
Department/Centre:	Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited:	18 Feb 2013 09:12
Last Modified:	18 Feb 2013 09:12
URI:	http://eprints.iisc.ac.in/id/eprint/45813

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