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Speech Enhancement using a Variable Level Decomposition DWT
National Academy Science Letters  (IF0.788),  Pub Date : 2020-08-16, DOI: 10.1007/s40009-020-00983-3
Samba Raju Chiluveru, Manoj Tripathy

The wavelet transform shows a promising solution for a non-stationary signal. The denoising of a noisy speech signal carried with a wavelet thresholding technique. The noisy signal decomposed into different frequency bands, and this decomposition level (DL) decided independent of non-stationary noise. In this letter, a new DL detection procedure presented, and it decides the decomposition level based on signal energy and speech dominance. The proposed DL applies to the speech denoising model, and the obtained results compared with the unversal thresholding technique and the minimum mean square error algorithm. The performance of the enhanced speech signal measures with speech intelligibility measure (STOI), and speech quality measure (PESQ). The experimental results revealed that the proposed scheme outperforms the conventional methods in all SNR and non-stationary environments.