AI for All Voices: A Scoping Review on Inclusive Pronunciation and Speaking AI Tools

Ervinda Dwi Meidyana(1*), Fayza Achsina Salsabila(2), Syahzanan Harris(3)


(1) Universitas Airlangga
(2) Universitas Airlangga
(3) Universitas Airlangga
(*) Corresponding Author

Abstract


English as a Foreign Language (EFL) learners often face challenges in developing speaking skills, including limited practice opportunities, pronunciation difficulties, and speaking anxiety. As artificial intelligence (AI) tools become more integrated into language education, they offer new ways to support speaking and pronunciation practice. However, multilingual and non-native learners remain underrepresented in developing and designing many of these tools. This scoping review examines how AI-assisted pronunciation technologies address inclusivity in EFL contexts, more specifically for multilingual learners. A total of 15 peer-reviewed articles published between 2021 and 2025 were retrieved from Scopus, ScienceDirect, and Web of Science. The findings show that AI tools generally enhance pronunciation accuracy, fluency, and learner motivation while offering personalized and flexible learning environments. Several tools also support affective inclusivity by reducing anxiety during speaking tasks. Yet, inclusivity is often a by- product rather than an intentional design goal. Persistent challenges include accent bias and a reliance on native-speaker training data, which can disadvantage multilingual learners. This review underscores the need for more inclusive and culturally responsive AI systems and provides a foundation for future research in equitable EFL pronunciation support.

Keywords


Artificial Intelligence; EFL learners; multilingual learners; inclusive education; pronunciation training

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