Speech Recognition Oriented Vowel Classification Using Temporal Radial Basis Functions
Computation and Language
2009-12-22 v1 Multimedia
Abstract
The recent resurgence of interest in spatio-temporal neural network as speech recognition tool motivates the present investigation. In this paper an approach was developed based on temporal radial basis function "TRBF" looking to many advantages: few parameters, speed convergence and time invariance. This application aims to identify vowels taken from natural speech samples from the Timit corpus of American speech. We report a recognition accuracy of 98.06 percent in training and 90.13 in test on a subset of 6 vowel phonemes, with the possibility to expend the vowel sets in future.
Keywords
Cite
@article{arxiv.0912.3917,
title = {Speech Recognition Oriented Vowel Classification Using Temporal Radial Basis Functions},
author = {Mustapha Guezouri and Larbi Mesbahi and Abdelkader Benyettou},
journal= {arXiv preprint arXiv:0912.3917},
year = {2009}
}