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This paper investigates the improvement of Telugu speech quality in terms of six objective quality measures using Discrete Wavelet Transform and proposes two Hybrid thresholding methods which are formed by combining soft and Improved thresholding methods with Modified Improved thresholding method. The performance of the new Hybrid methods is compared with the other thresholding methods. It is observed that the new proposed scheme yields better results when applied to Telugu noisy speech signals with low SNR (0dB) conditions. In this method, noisy speech signal is divided in to overlapping frames and each frame is windowed using hamming window. The windowed speech blocks are applied to the wavelet based speech enhancement algorithm and the enhanced speech is reconstructed in its time domain. For denoising the Telugu speech signal, various techniques like hard, soft, improved, modified improved and hybrid thresholding methods are used. Analysis is done using daubechies and symlets wavelets with different white Gaussian noise environments. Six Objective quality measures are considered in this study to test the performance of the algorithm for enhanced Telugu speech quality and compared. Hybrid thresholding methods perform better than hard, soft, improved and modified improved thresholding methods for wavelet based speech denoising.

Telugu Speech Enhancement In Terms Of Objective Quality Measures Using Discrete Wavelet Transform With Hybrid Thresholding