By Mohamed Hesham Farouk
This publication offers a survey on accepted of using wavelets research in numerous purposes of speech processing. the writer examines improvement and examine in several functions of speech processing. The booklet additionally summarizes the state-of-the-art study on wavelet in speech processing.
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Extra resources for Application of Wavelets in Speech Processing
Zhao, Q. Zhang, J. Dong, Robust pitch estimation using a wavelet variance analysis model. Signal Process. 89(6), 1216–1223 (2009) Chapter 10 Speech Coding, Synthesis, and Compression Abstract WT-based coding allows for the control of frequency resolution to closely match the response of the human auditory system. The inherent shaping of the wavelet synthesis filter and a controlled bit allocation to the wavelet coefficients help to minimize the perceptually significant noise due to the quantization error in the residual.
Appl. Sci. 53(5), 637–652 (2006) 4. A. Karmakar, A. K. Patney, A multiresolution model of auditory excitation pattern and its application to objective evaluation of perceived speech quality. IEEE Trans. Audio Speech Lang. Process. 14(6), 1912–1923 (2006) 5. W. Dobson, J. Yang, K. Smart, F. Guo, High quality low complexity scalable wavelet audio coding, in Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP’97), Apr 1997, pp. 327–330 6. F. H. S. Shyuu, Wavelet transforms for speech signal processing.
16(2), 171–179 (2013) 6. M. Joseph, P. Babu Anto, Speech compression using wavelet transform, in International Conference on Recent Trends in Information Technology (ICRTIT2011), (2011), pp. 754–758 7. M. Abo-Zahhad, A. M. Ahmed, High-quality low-complexity wavelet-based compression algorithm for audio signals. Electr. Eng. 86(4), 219–227 (2004) 8. M. Deriche, D. Ning, A novel audio coding scheme using warped linear prediction model and the discrete wavelet transform. IEEE Trans. Audio Speech Lang.