Author(s)

I A Maaly, A R Elobeid & K M Ali Ahmed

Abstract

A Hidden Markov Model (HMM) recognition system is implemented for Arabic Phonemes as units of recognition. An important result of this system is the confusion encountered between some phonemes of Arabic (e.g., /h/ (Ha), /?/ (Hamza)), i.e., the recognize could not distinguish between them. New parameters, which are based on a new classification of Arabic phonemes, are added at a higher level of the system for resolving this acoustic confusability and improving the recognition accuracy. These new parameters, which are based on the shape of the tongue and the place of articulation along the vocal tract, are called the Emphatic/nonemphatic, Root and Hamz parameters. The \“Emphatic/nonemphatic” parameter gives a performance of 44%, the \“Root” parameter gives a performance of 40%, while the \“Hamz” parameter could resolve confusability encountered between the phonemes /h/ and /?/ with a performance of 90%. These new parameters may need accurate estimates of the distances along the vocal tract to improve their performance. 1 Introduction The objective of this research is to achieve a robust recognition system for Arabic language. Arabic speech has its distinctive features, e.g., it has a large number of pharyngeal sounds (e.g., /x/ (Kha), /?/ (Hamza) and a large number of

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