Representation Of Arabic Pharyngeal Sounds Among Tamahaq Speakers In Al-hoggar : A Comparative Study Using Chatgpt
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Date
2026-06-10
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Revue algérienne des sciences du langage (RADSL)
Abstract
This study investigates the role of artificial intelligence (AI), particularly ChatGPT, in the phonetic representation of Arabic guttural consonants produced by Tamahaq-speaking learners of Arabic in Al-Hoggar region. As a pilot exploratory study, it combines contrastive analysis, error analysis, International Phonetic Alphabet (IPA)-based transcription, and acoustic analysis using Praat software to evaluate the relative accuracy of AI-generated phonetic representations. The acoustic analysis focused on formant frequencies (F1/F2), duration measurements, and spectrographic observation. The findings indicate that ChatGPT provides relatively accurate phonetic approximations for several consonants; however, important limitations remain, especially with pharyngeal consonants that are phonetically marked in Arabic. The study concludes that AI can support phonetic analysis and IPA-based transcription, although expert verification remains necessary.
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Keywords
Arabic guttural consonants, Tamahaq, IPA, ChatGPT, contrastive analysis, error analysis, Praat.
