Dynamic spectral subtraction on AWGN speech

To enable accurate exchange of information or data, the quality and intelligibility of speech play an important factor. However, pragmatically the quality of speech is distorted by the presence of background noise. This in turn leads to poor performance of the system as well as causes listener fatigue. To resolve such ambiguity we apply speech enhancement algorithms which improve the intelligibility as well as quality of speech which has been degraded by background noise.

In this paper two such algorithms have been discussed for noise reduction. One is conventional spectral subtraction method and the other is the proposed modified version of spectral subtraction. While the former aims to improve speech quality degraded by additive background noise, the latter aims to improve speech quality from dynamic additive noise as well. Modified noise reduction algorithm is compared to conventional spectral subtraction based on SNR improvement introduced by them.

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