BSS for improved interference estimation for blind speech signal extraction with two microphones

Zheng Y, Reindl K, Kellermann W (2009)

Publication Language: English

Publication Status: Published

Publication Type: Conference contribution, Conference Contribution

Publication year: 2009

Pages Range: 253-256

Article Number: 5413286

Event location: Aruba AN

ISBN: 978-1-4244-5179-1

DOI: 10.1109/CAMSAP.2009.5413286

Abstract

Blind Source Extraction (BSE) as desirable for acoustic cocktail party scenarios requires estimates for the target or interfering signals. Conventional single-channel approaches for obtaining the interference estimate rely on noise and interference estimates during absence of the target signal. For multichannel approaches using multiple microphone signals, a separation of simultaneously active target and interference signals becomes possible if the positions of the target and interfering sources are known. We propose a new method which exploits Directional BSS (Blind Source Separation with a geometric constraint) to estimate the interfering speech sources and diffuse background noise jointly and blindly. Herewith we can effectively deal with the underdetermined BSS scenario (more point sources than sensors) in reverberant environments and can even allow for additional babble noise in the background. © 2009 IEEE.

Authors with CRIS profile

Yuanhang Zheng Lehrstuhl für Multimediakommunikation und Signalverarbeitung (LMS) Klaus Reindl Professur für Signalverarbeitung Walter Kellermann Professur für Signalverarbeitung

How to cite

APA:

Zheng, Y., Reindl, K., & Kellermann, W. (2009). BSS for improved interference estimation for blind speech signal extraction with two microphones. In Proceedings of the 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2009 (pp. 253-256). Aruba, AN.

MLA:

Zheng, Yuanhang, Klaus Reindl, and Walter Kellermann. "BSS for improved interference estimation for blind speech signal extraction with two microphones." Proceedings of the 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2009, Aruba 2009. 253-256.

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