Improved Wiener Filter Algorithm for Speech Enhancement

Abstract

Most of the existing speech enhancement algorithms are aimed at improving the quality of speech, and the algorithms that can improve the speech intelligibility effectively are rare. Speech intelligibility has been found to improve listening comfort and it is generally related to the distortion of the speech signal closely. Studies have assessed the impact of speech distortion introduced by gain functions and shown that one of the main reasons that existing algorithms cannot improve speech intelligibility is because they allow amplification distortions more than 6dB. Therefore, these distortions of the enhanced amplitude spectrum should be corrected to improve the speech intelligibility. The early research by Loizou et al. obtained the experimental results on the ideal state and we are unable to use it in reality because there is no clean speech in reality. In this paper, we modify the method proposed by Loizou et al. and select the estimated speech under two hypothetical conditions to verify the improvement of the speech intelligibility. The short-term objective intelligibility value verifies the improvement of speech intelligibility as the improved algorithm of speech intelligibility is applied to reality successfully.

Vibe - With people with hearing impairment

“…Turget's work [29] focused on removing any distracting sounds from collected baby crying sounds and emphasizing speci ic points during the preprocessing stage. This pre-emphasis can done using spectral subtraction, Wiener iltering, and adaptive iltering [30,31]. The goal is to improve the Signal-to-Noise Ratio (SNR) of the sound ile.…”