الصوتيات
Volume 21, Numéro 2, Pages 43-62
2025-12-05
Multimodal Ai Interfaces For Arabic Phoneme Training: Addressing Efl Pronunciation Gaps
Authors : Hadef Chahida . Hadef Meriem .
Abstract
This study examines the integration of phonetic visualization tools in teaching Arabic phonemes to EFL learners, with a focus on the articulation of pharyngeal and emphatic sounds. Based on classroom observations and the analysis of 100 learner recordings, recurrent pronunciation difficulties were identified, particularly in distinguishing non-native sounds. Existing Arabic phonetics software often lacked clarity and dialectal adaptability. To bridge these gaps, a prototype multimodal interface was designed using real-time waveform feedback, animated vocal tract visuals, and IPA-based cues. Results showed improved learner performance and engagement, especially when visual and auditory feedback were combined. Learners appreciated features like waveform clarity, though some struggled with technical representations. The study highlights the value of multimodal instruction in phonetic training and suggests further development of AI-supported tools tailored to learner diversity. Future work will expand the tool’s capabilities and refine the user experience based on iterative classroom feedback.
Keywords
Arabic phonemes ; Phonetic visualization ; Emphatic sounds ; Multimodal interface ; EFL learners
Les articles similaires
شينون يحي
.
بن سعد محمد السعيد
.
ص 80-99.
Julianah Ajoke Akindele
.
Victor Ayomide Fabunmi
.
pages 381-396.
Kassim Alabani
.
Afful Jr. Benedict
.
pages 426-452.
Mounsi Younes
.
pages 975-983.
