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Speech Recognition of Arabic Spoken Digits
Author(s) -
Anas Allosh,
Nura Zlitni,
Ali Ganoun
Publication year - 2013
Publication title -
conference papers in engineering
Language(s) - English
Resource type - Journals
eISSN - 2314-5838
pISSN - 2314-5366
DOI - 10.1155/2013/130473
Subject(s) - computer science , speech recognition , arabic , natural language processing , cepstrum , mel frequency cepstrum , artificial intelligence , speaker recognition , feature extraction , linguistics , philosophy
With the widespread growth in the use of digital computers, there has been an increasing need to be able to communicate with machines in a simple manner. One of the main tasks that simplify the communication with machines is the speech recognition. Speech recognition is the translation of spoken words into text. However, speech recognition is a very complex problem. This paper is related to the recognition of spoken Arabic digits. Two recognition techniques have been implemented and tested: Pitch Detection Algorithm (PDA) and Cepstrum Correlation Algorithm (CCA). In order to analyze the recognition accuracy of the selected techniques, a database of spoken Arabic digits has been created. The performance of the two techniques has been analyzed based on the created database.

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