Speech Enhancement Through an Optimized Subspace Division Technique

Abstract

The speech enhancement techniques are often employed to improve the quality and intelligibility of the noisy speech signals. This paper discusses a novel technique for speech enhancement which is based on Singular Value Decomposition. This implementation utilizes a Genetic Algorithm based optimization method for reducing the effects of environmental noises from the singular vectors as well as the singular values of a noise-corrupted speech. The presented article also reviews the existing algorithms for subspace division and carries out extensive sets of experiments to clearly show the efficiency of the proposed method in comparison with the other superior speech enhancement approaches.