A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Ten lectures on wavelets
Wavelets and subband coding
On color transforms and bit allocation for optimal subband image compression
Image Communication
Using Lossless Data Compression in Data Storage Systems: Not for Saving Space
IEEE Transactions on Computers
Modeling the Temporal Evolution of Acoustic Parameters for Speech Emotion Recognition
IEEE Transactions on Affective Computing
Speech Compression by Polynomial Approximation
IEEE Transactions on Audio, Speech, and Language Processing
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
International Journal of Speech Technology
A pitch synchronous approach to design voice conversion system using source-filter correlation
International Journal of Speech Technology
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In this paper, optimized wavelet filters for speech compression are proposed whose wavelet filter coefficients are derived with different window techniques such as Kaiser and Blackman windows via simple linear optimization. When the developed wavelet filters are exploited for speech compression, they not only give better compression ratio but also yield good fidelity parameters as compared to other wavelet filters. A comparative study of performance of different existing wavelet filters and the proposed wavelet filters is made in terms of compression ratio (CR), signal-to-noise ratio (SNR), peak signal-to-noise ratio (PSNR) and normalized root-mean square error (NRMSE) at different thresholding levels. The simulation result included in this paper shows increased efficacy and improved performance of the proposed filters in the field of speech signal processing.