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Evolutionary structure of hidden Markov models for audio-visual Arabic speech recognition
by Amina Makhlouf; Lilia Lazli; Bachir Bensaker
International Journal of Signal and Imaging Systems Engineering (IJSISE), Vol. 9, No. 1, 2016


Abstract: In this paper, we present an Audio-Visual Automatic Speech Recognition System that combines the acoustic and the visual data. The proposed algorithm here, for modelling the multimodal data, is a Hidden Markov Model (HMM) hybridised with the Genetic Algorithm (GA) to determine its optimal structure. This algorithm is combined with the Baum-Welch algorithm, which allows an effective re-estimation of the probabilities of the HMM. Our experiments show the improvement in the performance of the most promising audio-visual system, based on the combination of GA/HMM model compared to the traditional HMM.

Online publication date: Mon, 08-Feb-2016


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