Discrete-time signal processing
Discrete-time signal processing
Ten lectures on wavelets
Fundamentals of speech recognition
Fundamentals of speech recognition
IEEE Spectrum
IEEE Computational Science & Engineering
Speech compression with cosine and wavelet packet near-best bases
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 01
Simple and powerful instrument model for the source separation of polyphonic music
WSEAS Transactions on Signal Processing
A new approach in wavelet based speech compression
MAMECTIS'08 Proceedings of the 10th WSEAS international conference on Mathematical methods, computational techniques and intelligent systems
Theoretical equivalency and practical advantages of wavelet based paradigms in signal processing
NEHIPISIC'11 Proceeding of 10th WSEAS international conference on electronics, hardware, wireless and optical communications, and 10th WSEAS international conference on signal processing, robotics and automation, and 3rd WSEAS international conference on nanotechnology, and 2nd WSEAS international conference on Plasma-fusion-nuclear physics
Locating zeros of polynomials associated with Daubechies orthogonal wavelets
WSEAS Transactions on Mathematics
WSEAS Transactions on Signal Processing
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In this paper, various speech processing techniques in time, time-frequency and time-scale domains for the purposes of recognition and compression are displayed. The examination of the human cochlea is included revealing practice of Wavelet Transform representation. The interchange between theory and application is displayed in a variety of work that have been accomplished in that direction. In particular, we emphasize the role of Wavelet Transforms in recognizing and compressing speech signals.