A robust speech enhancement method in noisy environments

Abstract

Speech enhancement aims to eliminate or reduce undesirable noises and distortions, this processing should keep features of the speech to enhance the quality and intelligibility of degraded speech signals. In this study, we investigated a combined approach using single-frequency filtering (SFF) and a modified spectral subtraction method to enhance single-channel speech. The SFF method involves dividing the speech signal into uniform subband envelopes, and then performing spectral over-subtraction on each envelope. A smoothing parameter, determined by the a-posteriori signal-to-noise ratio (SNR), is used to estimate and update the noise without the need for explicitly detecting silence. To evaluate the performance of our algorithm, we employed objective measures such as segmental SNR (segSNR), extended short-term objective intelligibility (ESTOI), and perceptual evaluation of speech quality (PESQ). We tested our algorithm with various types of noise at different SNR levels and achieved results ranging from 4.24 to 15.41 for segSNR, 0.57 to 0.97 for ESTOI, and 2.18 to 4.45 for PESQ. Compared to other standard and existing speech enhancement methods, our algorithm produces better results and performs well in reducing undesirable noises.