(untitled) (International Journal of Engineering and Computer Science, 2015)
The term “Speech Enhancement” refereed as to improve quality or intelligibility of speech signal. Speech signal is often degraded by additive background noise like babble noise, train noise, restaurant noise etc. In such noisy environment listening task is very difficult at the end user. Many times speech enhancement is used for pre processing of speech for computer speech recognition system. In this method, the noise spectrum is estimated during speech pauses, and is subtracted from the noisy speech spectrum to estimate the clean speech. This is also achieved by multiplying the noisy speech spectrum with a gain function and later combining it with the phase of the noisy speech. The drawback of this method is the presence of processing distortions, called remnant noise. A number of variations of the method have been developed over the past years to address the drawback. These variants form a family of spectral subtractive-type algorithms. The aim of this paper is to provide a comparison and simulation study of the different forms of subtraction-type algorithms viz. basic spectral subtraction, Modified Spectral Subtraction , multi-band spectral subtraction, iterative spectral subtraction, and spectral subtraction based on perceptual properties.