Effect of Singular Value Decomposition Based Processing on Speech Perception

Abstract

Speech is an important biological signal forprimary mode of communication among human being and also the most natural and efficientform of exchanging information among human in speech. Speech processing is the most important aspect in signal processing.In this paper the theory of linear algebra calledsingular value decomposition (SVD) is applied to the speech signal. SVD is a technique for deriving important parameters of a signal. The parameters derived usingSVD may further be reduced by perceptual evaluation of the synthesized speech using only perceptual ly important parameters, where the speech signal can be compressed so that the information can be transformed into compressed form without losing its quality. This technique finds wide applications in speech compression, speech recognition,and speech synthesis. The objective of this paper is to investigate the effect of SVD basedfeature selection of the input speech on the perception of theprocessed speech signal. The speech signal which is in the form of vowels \a\, \e\, \u were recorded from each of the six speakers (3males and 3 females). The vowels for the six speakers were analyzed using SVD based processing and the effect of the reduction in singular values was investigated on the perception of the resynthesized vowels using reduced singular values. Investigations have shown that the number of singular values can be drasti cally reduced without significantly affecting the perception of the vowels.