Integration of AI-Based Text-to-Speech Technology in Arabic Listening Skills Learning

The advancement of modern technology has brought significant innovations in the field of education. One of the most developed technologies is AI-based Text-to-Speech (TTS), which converts written text into natural, accurate speech. This technology effectively solves the challenges students face in developing listening skills (maharah istima'). This research analyzes the potential, challenges, and strategies in integrating AI-based TTS into Arabic language learning, particularly in enhancing maharah istima'. The study uses a qualitative approach with a library research method. Data sources are obtained from relevant and up-to-date scientific literature, including journal articles, books, proceedings, and research reports. The collected data is analyzed using a thematic analysis approach. The findings show that AI-based TTS can improve the effectiveness of learning maharah istima' in Arabic, offering greater accessibility and flexibility. However, further development is needed to address limitations such as prosody, dialect, and the application of tajwid. One of the key strategies is implementing deep learning models in TTS.