An expert system for speaker identification using adaptive wavelet sure entropy
Expert Systems with Applications: An International Journal
The speaker identification by using genetic wavelet adaptive network based fuzzy inference system
Expert Systems with Applications: An International Journal
Wavelet entropy and neural network for text-independent speaker identification
Engineering Applications of Artificial Intelligence
A multi-resolution multi-classifier system for speaker verification
Expert Systems: The Journal of Knowledge Engineering
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A new wavelet representation is explored. The transform is based on a pitch-synchronous vector representation and it adapts to the oscillatory or aperiodic characteristics of signals. Pseudo-periodic signals are represented in terms of an asymptotically periodic trend and aperiodic fluctuations at several scales. The transform reverts to the ordinary wavelet transform over totally aperiodic signal segments. The pitch-synchronous wavelet transform is particularly suitable to the analysis, rate-reduction coding and synthesis of speech signals and it may serve as a preprocessing block in automatic speech recognition systems. Feature extraction such as separation of voice from noise in voiced consonants is easily performed by means of partial wavelet expansions. A stochastic model of aperiodic fluctuations is proposed