A new speech signal denoising algorithm using common vector approach

Speech denoising may improve intelligibility of speech and hearing comfort in voice communication/recognition applications in noisy environments. It can also be used to enhance old recordings. Most speech enhancement methods are intrusive and cause some loss in the signal component while removing noise. In this paper, we propose a method based on common vector approach (CVA) for reducing losses in single-channel enhancement algorithms. In the proposed technique, overlapping speech sample frames are collected in classes according to their similarity and common and difference vectors of the classes are separated using CVA. Since the noise component is uncorrelated and therefore presumably concentrated in the difference part, difference vectors are denoised using a common denoising technique and sample frames are reconstructed by combining the common and the denoised difference parts. This operation does not affect the common vector and somewhat secures improvement even for highly noised data. Compared to the state-of-the-art, highly promising results are obtained in terms of several speech quality measures.