USING ARTIFICIAL INTELLIGENCE IN ARTICULATION EXERCISES FOR SPEECH DISORDERS

Authors

DOI:

https://doi.org/10.63034/esr-513

Keywords:

artificial intelligence, speech disorders, articulation exercises, speech therapy, digital tools, inclusive education

Abstract

This article explores the use of Artificial Intelligence (AI) in articulation exercises for children with speech disorders. Speech development is a key aspect of early childhood education, and articulation difficulties can significantly affect communication and learning outcomes. AI-based tools, including speech recognition, interactive mobile applications, and adaptive learning systems, provide innovative opportunities for personalized correction and practice. These technologies allow children to receive immediate feedback on pronunciation, monitor progress, and engage in motivating, game-like training environments. The study highlights how AI can support speech therapists and educators by automating repetitive exercises, offering individualized learning trajectories, and tracking improvements over time. International experiences in speech therapy supported by AI are examined, and practical recommendations for implementation in the Kazakhstani context are provided. The findings demonstrate that AI integration enhances the efficiency of articulation training, supports inclusive education, and contributes to the overall development of communication skills in children with speech disorders.

References

Әбілдаева, Ж. "Қазақ тілінде сөйлеу бұзылыстары мен олардың түзету әдістері". – Алматы: 2018.

Айтпаева, Б. "Қазақ тіліндегі логопедиялық әдістемелер". – Алматы: 2019.

Қазақ тілі грамматикасы**: Ж. Құрманов. "Қазақ тілі грамматикасы". Алматы, 2018.

Логопедия және сөйлеу тілі бұзылыстары**: Айтпаева, Б. "Логопедиялық әдістемелер". Алматы, 2020.

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Published

2025-09-11

How to Cite

Yesenkul, A. (2025). USING ARTIFICIAL INTELLIGENCE IN ARTICULATION EXERCISES FOR SPEECH DISORDERS. Eurasian Science Review An International Peer-Reviewed Multidisciplinary Journal, 3(5), 70–77. https://doi.org/10.63034/esr-513