Different Approaches of Spectral Subtraction method for Enhancing the Speech Signal in Noisy Environments

Enhancement of speech signal degraded by additive background noise has received more attention over the past decade, due to wide range of applications and limitations of the available methods. Main objective of speech enhancement is to improve the perceptual aspects of speech such as overall quality, intelligibility and degree of listener fatigue. Among the all available methods the spectral subtraction algorithm is the historically one of the first algorithm, proposed for background noise reduction. The greatest asset of Spectral Subtraction Algorithm lies in its simplicity. The simple subtraction process comes at a price. More papers have been written describing variations of this algorithm that minimizes the shortcomings of the basic method than other algorithms. In this paper we present the review of basic spectral subtraction Algorithm, a short coming of basic spectral subtraction Algorithm, different modified approaches of Spectral Subtraction Algorithms such as Spectral Subtraction with over subtraction factor, Non linear Spectral Subtraction, Multiband Spectral Subtraction, Minimum mean square Error Spectral Subtraction, Selective Spectral Subtraction, Spectral Subtraction based on perceptual properties that minimizes the shortcomings of the basic method, then performance evaluation of various modified spectral subtraction Algorithms, and