Multi-band based recognition of spoken Arabic numerals using wavelet transform

Automatic speech recognition (ASR) using multi-band decoruposition provides high recognition rates especially in noisy environments. The Discrete Wavelet Transform (DWT) is known to be an efficient tool for decomposing signals into frequency sub-bands;g In this paper, the concept of Feature Recombination (FC) as applied to the recognition of spoken Arabic numerals is suggested. Utterances are decomposed using DWT before Cepstral coefficients of the resulting sub-bands are calculated. The obtained coefficients are concatenated to form a single feature vector that is used as an input to the speech classifier, e.g. a Hidden Markov Model (HMM), to compute the likelihood. Simulation results have demonstrated that the achieved correct recognition rates using the suggested method are comparable with the full-band ASR (conventional) system.