Radial basis functions with wavelet packets for recognizing Arabic speech

Authors:
Jalal Karam
Affiliations:
Faculty of Science and General Studies, Alfaisal University, Riyadh, Kingdom of Saudi Arabia
Venue:
CSECS '10 Proceedings of the 9th WSEAS international conference on Circuits, systems, electronics, control & signal processing
Year:
2010

Citing 2
Cited 2

Review of neural networks for speech recognition

Neural Computation
Wavelets and subband coding

Wavelets and subband coding

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
Biorthoganal wavelet packets and Mel scale analysis for automatic recognition of Arabic speech via radial basis functions

WSEAS Transactions on Signal Processing

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Abstract

In this paper, a Neural Network (NN) approach for the recognition of the Arabic digits is presented. The two phases of training and testing in a Radial Basis Functions (RBF) type network is described. Bi-Orthogonal Wavelets are constructed and used for analysis of generated subwords of the digits. This approach decomposes spoken Arabic digits based on the acoustical information contained within the speech signals. The procedure locates the boundaries between subwords by finding the peaks in the function representing the spectral change between consecutive speech frames. Then, the Frame-based energy parameters derived from a Wavelet Packet Scale (WPS) are used in deriving the Spectral Variation Function (SVF).