A Wavelet Neural Network Ramwork for Speaker Idntifcation | ||
| Journal of Engineering | ||
| Article 1, Volume 12, Issue 1, March 2006, Pages 227-236 | ||
| Authors | ||
| Saleem M-R. Taha; Dhiadeen M. Salih; W.A. Mahmoud | ||
| Abstract | ||
| This paper introduces a new model-free identification methodology to detect and identify speakers and recognize them. The basic module of the methodology is a novel multi-dimensional wavelet neural network . The WNN approach include: a universal approximator ; the time – frequency localization : property of wavelets leads to reduced networks at a given level of performance ; The construct used as the feature mode classifier . Wavelet transform has been successfully applied to the processing of non – stationary speech signal and the feature vector that obtained becomes the input to the wavelet neural network which is trained off-line to map features to used for the classification procedure. An example is employed to illustrate the robustness and effectiveness of proposed scheme. | ||
| Keywords | ||
| speaker identification; Speaker Recognition; wavelet neural network; Wavelet Transform; discrete wavelet transform; Back; propagation algorithm | ||
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