A Family of Maximum SNR Filters for Noise Reduction

Gongping Huang, Jacob Benesty, Tao Long, Jingdong Chen

Research output: Contribution to journalJournal articleResearchpeer-review

25 Citations (Scopus)

Abstract

This paper is devoted to the study and analysis of the maximum signal-to-noise ratio (SNR) filters for noise reduction both in the time and short-time Fourier transform (STFT) domains with one single microphone and multiple microphones. In the time domain, we show that the maximum SNR filters can significantly increase the SNR but at the expense of tremendous speech distortion. As a consequence, the speech quality improvement, measured by the perceptual evaluation of speech quality (PESQ) algorithm, is marginal if any, regardless of the number of microphones used. In the STFT domain, the maximum SNR filters are formulated by considering the interframe information in every frequency band. It is found that these filters not only improve the SNR, but also improve the speech quality significantly. As the number of input channels increases so is the gain in SNR as well as the speech quality. This demonstrates that the maximum SNR filters, particularly the multichannel ones, in the STFT domain may be of great practical value.
Original languageEnglish
JournalIEEE/ACM Transactions on Audio, Speech, and Language Processing
Volume22
Issue number12
Pages (from-to)2034 - 2047
Number of pages14
ISSN2329-9290
DOIs
Publication statusPublished - 26 Sept 2014

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