Subjective Comparison of Speech Enhancement Algorithms

Abstract

We report on the development of a noisy speech corpus suitable for evaluation of speech enhancement algorithms. This corpus is used for the subjective evaluation of 13 speech enhancement methods encompassing four classes of algorithms: spectral subtractive, subspace, statistical-model based and Wiener algorithms. The subjective evaluation was performed by Dynastat, Inc. using the ITU-T P.835 methodology designed to evaluate the speech quality along three dimensions: signal distortion, noise distortion and overall quality. This paper reports the results of the subjective tests