Automatic Pronunciation Assessment and Feedback for Arabic Learners: A Review

The world has become a global village, and mastering multiple languages has become necessary; therefore, the need for computer-assisted language learning (CALL) applications is growing. Speech being the most spontaneous and widespread mode of communication and learning pronunciation occupies a considerable place, and computer-assisted pronunciation teaching (CAPT) is increasingly integrated into CALL systems. Herein, pronunciation assessment is a critical component that aims to detect and diagnose mispronunciation to provide informative feedback for the learners. On the other hand, Arabic is among the top five languages to learn, but it is sorely lacking in resources for CAPT. This paper aims to bridge the gap between Arabic and high-resource languages in CAPT. As neither a review nor a survey on pronunciation assessment for Arabic exists, this paper provides an overview of the existing research on automatic pronunciation assessment and feedback for Arabic. Many studies are addressed based on three main tasks: pronunciation rating, mispronunciation detection and diagnosis (MDD), and feedback. The paper summarizes existing findings of Arabic pronunciation assessment, underlines challenges, and sheds some light on the opportunities offered to researchers on the topic.