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Automatic recognition of spoken alphabets is one of the difficult tasks in the field of computer speech recognition. In this research, spoken Arabic alphabets are investigated from the speech recognition problem point of view. The system is designed to recognize spelling of an isolated word. The Hidden Markov Model Toolkit (HTK) is used to implement the isolated word recognizer with phoneme based...
Important research areas, such as automatic speech recognition, optical character recognition, and information retrieval, heavily depend on the presence of a good statistical representation of the used language. A more precise representation leads to more accurate systems. However, Arabic is a richer and more complex language than English. Moreover, clitics have a heavy presence in the Arabic language...
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