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A Conceptual Framework for Noise ReductionBinaural Noise Reduction in the Time Domain

A Conceptual Framework for Noise Reduction: Binaural Noise Reduction in the Time Domain [Binaural noise reduction is an important problem in applications where there is a need to produce two “clean” outputs from noisy observations picked up by multiple microphones. But the mitigation of the noise should be made in such a way that no audible distortion is added to the two outputs (this is the same as in the single-channel case) and meanwhile the spatial information of the desired sound source should be preserved so that, after noise reduction, the remote listener will still be able to localize the sound source thanks to his/her binaural hearing mechanism. In this chapter, we approach this problem with the widely linear theory in the time domain, where both the temporal and spatial information is exploited.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

A Conceptual Framework for Noise ReductionBinaural Noise Reduction in the Time Domain

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Publisher
Springer International Publishing
Copyright
© The Author(s) 2015
ISBN
978-3-319-12954-9
Pages
51 –65
DOI
10.1007/978-3-319-12955-6_5
Publisher site
See Chapter on Publisher Site

Abstract

[Binaural noise reduction is an important problem in applications where there is a need to produce two “clean” outputs from noisy observations picked up by multiple microphones. But the mitigation of the noise should be made in such a way that no audible distortion is added to the two outputs (this is the same as in the single-channel case) and meanwhile the spatial information of the desired sound source should be preserved so that, after noise reduction, the remote listener will still be able to localize the sound source thanks to his/her binaural hearing mechanism. In this chapter, we approach this problem with the widely linear theory in the time domain, where both the temporal and spatial information is exploited.]

Published: Apr 1, 2015

Keywords: Noise Reduction; Microphone Array; Widely Linear; TIMIT Database; Complex Random Variable

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