Evaluation of noise estimation techniques for single-channel speech in low SNR noise environment

Abstract

This paper investigates the performance capability of noise estimation techniques for single-channel speech. These techniques are evaluated in presence of low SNR noises (i. e. f16, babble, white, and pink). The noise estimation techniques have major impact on the quality and intelligibility of denoised speech pattern. The noise estimation techniques are evaluated in frequency domain in terms of quality and intelligibility measure parameters. The Perceptual Evaluation of Speech Quality (PESQ), Weighted Spectral Slop metric (WSS), Frequency Weighted Segmental SNR (fw-SNRseg), Speech Intelligibility Index (SII), and output SNR parameters are used for performance evaluation of low SNR noises mixed speech patterns. The sampling frequency used for processing is 8000 Hz and all algorithms are implemented in MATLAB 7.14.