Title :
A Family of Maximum SNR Filters for Noise Reduction
Author :
Gongping Huang ; Benesty, Jacob ; Tao Long ; Jingdong Chen
Author_Institution :
Center of Immersive & Intell. Acoust., Northwestern Polytech. Univ., Xian, China
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.
Keywords :
Fourier transforms; filtering theory; microphones; signal denoising; PESQ algorithm; STFT domain; interframe information; maximum SNR filter; microphone; noise reduction; perceptual evaluation of speech quality algorithm; short-time Fourier transform domain; signal-to-noise ratio filter; speech distortion; speech quality improvement; Correlation; Microphones; Noise reduction; Signal to noise ratio; Speech; Vectors; Maximum SNR filter; multichannel; noise reduction; short-time Fourier transform (STFT) domain; single channel; speech enhancement; time domain;
Journal_Title :
Audio, Speech, and Language Processing, IEEE/ACM Transactions on
DOI :
10.1109/TASLP.2014.2360643