On the enhancement of dereverberation algorithms using multiple perceptual-evaluation criteria

Abstract

This paper describes an enhancement strategy based on several perceptual-assessment criteria for dereverberation algorithms. The complete procedure is applied to an algorithm for reverberant speech enhancement based on single-channel blind spectral subtraction. This enhancement was implemented by combining different quality measures, namely the so-called QAreverb, the speech-to-reverberation modulation energy ratio (SRMR) and the perceptual evaluation of speech quality (PESQ). Experimental results, using a 4211-signal speech database, indicate that the proposed modifications can improve the word error rate (WER) of speech recognition systems an average of 20%.