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A generalized Stein's estimation approach to speech enhancement based on perceptual criteria

Krishnan, Sunder Ram and Seelamantula, Chandra Sekhar (2012) A generalized Stein's estimation approach to speech enhancement based on perceptual criteria. In: Workshop on Statistical and Perceptual Audition (SAPA) - Speech Communication with Adaptive Learning (SCALE), September 11, 2012, Bangalore, Karnataka, India.

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Abstract

We address the problem of speech enhancement using a risk- estimation approach. In particular, we propose the use the Stein’s unbiased risk estimator (SURE) for solving the problem. The need for a suitable finite-sample risk estimator arises because the actual risks invariably depend on the unknown ground truth. We consider the popular mean-squared error (MSE) criterion first, and then compare it against the perceptually-motivated Itakura-Saito (IS) distortion, by deriving unbiased estimators of the corresponding risks. We use a generalized SURE (GSURE) development, recently proposed by Eldar for MSE. We consider dependent observation models from the exponential family with an additive noise model,and derive an unbiased estimator for the risk corresponding to the IS distortion, which is non-quadratic. This serves to address the speech enhancement problem in a more general setting. Experimental results illustrate that the IS metric is efficient in suppressing musical noise, which affects the MSE-enhanced speech. However, in terms of global signal-to-noise ratio (SNR), the minimum MSE solution gives better results.

Item Type: Conference Paper
Additional Information: Copyright of this article belongs to International Computer Science Institute (ICSI).
Keywords: Stein’s Unbiased Risk Estimator (SURE); Perceptual Distortion Metrics; Generalized SURE (GSURE); Speech Enhancement
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Depositing User: Id for Latest eprints
Date Deposited: 02 Jul 2013 06:56
Last Modified: 02 Jul 2013 06:56
URI: http://eprints.iisc.ac.in/id/eprint/46540

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