2007Unpublished venueRequires access

The effect of the additivity assumption on time and frequency domain wiener filtering for speech enhancement

Kamil Wójcicki, Stephen So, Kuldip K. Paliwal

Open publisher page 1 citations

Abstract

In this paper, we investigate the validity of the common assumption made in Wiener filtering that the clean speech and noise signals are uncorrelated under short-time analysis typically used for speech enhancement. In order to achieve this we have performed speech enhancement experiments, where speech corrupted by additive white Gaussian noise is enhanced by a Wiener filter designed in the time as well as the frequency domains. Results of oracle-style experiments confirm that the inclusion of the additivity assumption in Wiener filtering results in negligible degradation of enhanced speech quality. Informal listening tests show that the background noise resulting from time domain enhancement to be more tolerable than the background noise resulting from frequency domain framework. Index Terms: Wiener filtering, speech enhancement 1.

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What this paper is about

In this paper, we investigate the validity of the common assumption made in Wiener filtering that the clean speech and noise signals are uncorrelated under short-time analysis typically used for speech enhancement. In order to achieve this we have performed speech enhancement experiments, where speech corrupted by additive white Gaussian noise is enhanced by a Wiener filter designed in the time as well as the frequency domains. Results of oracle-style experiments confirm that the inclusion of the additivity assumption in Wiener filtering results in negligible degradation of enhanced speech quality. Informal listening tests show that the background noise resulting from time domain enhancement to be more tolerable than the background noise resulting from frequency domain framework. Index Terms: Wiener filtering, speech enhancement 1.

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Available abstract

In this paper, we investigate the validity of the common assumption made in Wiener filtering that the clean speech and noise signals are uncorrelated under short-time analysis typically used for speech enhancement. In order to achieve this we have performed speech enhancement experiments, where speech corrupted by additive white Gaussian noise is enhanced by a Wiener filter designed in the time as well as the frequency domains. Results of oracle-style experiments confirm that the inclusion of the additivity assumption in Wiener filtering results in negligible degradation of enhanced speech quality. Informal listening tests show that the background noise resulting from time domain enhancement to be more tolerable than the background noise resulting from frequency domain framework. Index Terms: Wiener filtering, speech enhancement 1.

Key concepts: Wiener filter, Speech enhancement, Wiener deconvolution, Speech recognition, White noise, Computer science, Noise (video), Gaussian noise

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