Building an Assistant Mobile Application for Teaching Arabic Pronunciation Using a New Approach for Arabic Speech Recognition
نویسنده
چکیده
The Arabic language is characterized by its vocal variations. Making its pronunciation a difficult task for Arabic learners. In this paper, we show how we built a mobile application that can detect mispronounced words and guide the user to the correct pronunciation. Foreigners and children can learn Arabic pronunciation in a friendly manner using our application. Our mobile application is customized to help them learn The Holy Quran recitation in particular. The process of the application compares the user sound (sound signal) of a single word with the set of correct recordings of this word pronunciation. This paper proposes the use of MFCC features to extract features from the speech signal. It also demonstrates the use of a modified version of DTW algorithm to compare the features of the user and the teacher.
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