Abjad: Towards Interactive Learning Approach to Arabic Reading Based on Speech Recognition

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Abstract

Speech recognition technology has gained more attention recently especially with the increasing use of mobile phones, and tablets. Yet, researches in speech recognition technology for Arabic language is still limited. This paper presents our experience with Arabic speech recognition using Android's SpeechRecognizer Application Program Interface (API) through the design and implementation of Abjad. Abjad is a mobile application for learning Arabic reading which mainly targets children at the age of six years old. It interacts with the users in a real-time manner by prompting them to record their voice while reading. The voice is then instantly evaluated and vocal feedback is provided according the accuracy of the user reading. In addition, the users can do tests to assess their progress in reading. The main goals of Abjad are to provide the Arabic language learner in general, and primary one children in particular with interactive technology to shorten their learning journey. More importantly, to enrich the Arabic speech recognition researches with our experience using SpeechRecpgnizer API for Arabic language, including the optimization techniques we developed to increase the accuracy rate of Arabic speech recognition from 44.44% to up to 94.44% with adults and 80% with children.

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APA

Alsunaidi, N., Alzeer, L., Alkatheiri, M., Habbabah, A., Alattas, M., Aljabri, M., & Altassan, M. (2018). Abjad: Towards Interactive Learning Approach to Arabic Reading Based on Speech Recognition. In Procedia Computer Science (Vol. 142, pp. 198–205). Elsevier B.V. https://doi.org/10.1016/j.procs.2018.10.476

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