EMD BASED SPEECH ENHANCEMENT USING SOFT AND HARD THRESHOLD TECHNIQUES

Abstract

In last few decades many attempts have been made on speech signals to eliminates the noise. Purpose of use any speech enhancement algorithm is to eliminate noises in variety of environments; most prominent of which are telecommunication applications. The purpose of this paper is to development of a novel speech enhancement algorithm which offers superior noise reduction over current methods. This Research paper work demonstrates a novel time domain speech enhancement algorithm for speech signals called empirical mode decomposition (EMD). EMD decomposes the speech signal corrupted by noise signal into a finite number of band limited signals known as intrinsic mode functions (IMFs), using iterative procedure called sifting process. These IMFs are denoised by using two different techniques first method is IMFs thresholding method or direct method of speech enhancement and another technique is IMF frame based method are discussed in this work. Both the methods use soft and hard threshold techniques for denoising the IMFs which are obtained from EMD. These algorithms are implemented empirically by using MATLAB software on real time speech data. Experimental Results shows that IMFs frame based method superior than direct method this can be tested by adding noises with the different SNR values to the clean speech.