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Dr. Mohamed Husien Mohamed Eid :: Publications:

Arabic Phonemes Recognition using HMM
Authors: M. H. El-Sayed; M.H. Eid; W. A. Sultan
Year: 2022
Keywords: Arabic Speech Recognition; Phonemes; Phoneme Model; Viterbi Algorithm; HMM; Gaussian Mixtures; Acoustics.
Journal: Not Available
Volume: Not Available
Issue: Not Available
Pages: Not Available
Publisher: Not Available
Local/International: Local
Paper Link: Not Available
Full paper Not Available
Supplementary materials Not Available

Arabic Language is one of the most widely-spoken languages in the world, Arabic Speech Recognition is one of the topics that need more attention from the research community. In this paper we use Hidden-Markov modeling (HMM) to develop an efficient phoneme recognition engine for Arabic. An HMM has been trained on ELRA Database and we study the effect of different parameters included in the decoding Algorithm known as Viterbi. The effect of increasing the number of Gaussian Mixtures components is also studied in output density of HMM. Results of each case has been presented and suggestions for enhancing performance have been also introduced.

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