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Fundamentals of Speech EnhancementBest Speech Enhancement Estimator in the Time Domain

Fundamentals of Speech Enhancement: Best Speech Enhancement Estimator in the Time Domain [In this chapter, we study the best speech enhancement estimator in the time domain. The first part focuses on the single-channel scenario, where important insights are given thanks to different kinds of correlation coefficients; in the linear case, we obtain the well-known Wiener filter whose functioning is explained within this general framework. The second part deals with the best binaural speech enhancement estimator; the approach taken here is by the reformulation of the binaural problem into a monaural one thanks to complex random variables.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Fundamentals of Speech EnhancementBest Speech Enhancement Estimator in the Time Domain

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Publisher
Springer International Publishing
Copyright
© The Author(s) 2018
ISBN
978-3-319-74523-7
Pages
23 –44
DOI
10.1007/978-3-319-74524-4_3
Publisher site
See Chapter on Publisher Site

Abstract

[In this chapter, we study the best speech enhancement estimator in the time domain. The first part focuses on the single-channel scenario, where important insights are given thanks to different kinds of correlation coefficients; in the linear case, we obtain the well-known Wiener filter whose functioning is explained within this general framework. The second part deals with the best binaural speech enhancement estimator; the approach taken here is by the reformulation of the binaural problem into a monaural one thanks to complex random variables.]

Published: Feb 10, 2018

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