Authors

  • Nishona Boymurodova
    Bukhara State Pedagogical Institute

DOI:

https://doi.org/10.71337/inlibrary.uz.ijai.120505

Abstract

This article explores the role of Artificial Intelligence (AI)-powered feedback systems in enhancing speaking and pronunciation skills in English language learners. With increasing access to digital tools, AI has emerged as a transformative force in language education. The paper discusses the key functionalities, pedagogical advantages, and limitations of AI-based pronunciation trainers and speech recognition tools. It also examines empirical findings from recent studies and highlights the implications for learners, teachers, and curriculum developers.

 

 

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INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE

ISSN: 2692-5206, Impact Factor: 12,23

American Academic publishers, volume 05, issue 06,2025

Journal:

https://www.academicpublishers.org/journals/index.php/ijai

page 1545

AI-POWERED FEEDBACK SYSTEMS IN SPEAKING AND PRONUNCIATION

TRAINING: BENEFITS AND DRAWBACKS

Boymurodova Nishona

Bukhara State Pedagogical Institute, Uzbekistan

Email:

boymurodovanishona51@gmail.com

Abstract:

This article explores the role of Artificial Intelligence (AI)-powered feedback systems

in enhancing speaking and pronunciation skills in English language learners. With increasing

access to digital tools, AI has emerged as a transformative force in language education. The

paper discusses the key functionalities, pedagogical advantages, and limitations of AI-based

pronunciation trainers and speech recognition tools. It also examines empirical findings from

recent studies and highlights the implications for learners, teachers, and curriculum developers.

Keywords:

Artificial Intelligence, pronunciation, speaking skills, feedback systems, speech

recognition, ELT

Introduction

Speaking and pronunciation are critical aspects of language proficiency. However, traditional

classroom settings often lack the resources and time needed for individualized pronunciation

training. The emergence of AI-powered tools, such as automatic speech recognition (ASR)

systems and intelligent tutoring systems (ITS), offers new possibilities for personalized,

immediate feedback on learners’ oral performance. This paper aims to examine how AI-

powered feedback systems contribute to the development of speaking and pronunciation skills.

AI in Pronunciation Training

AI in pronunciation training is typically implemented through mobile applications, web-based

platforms, or embedded classroom software. These systems utilize speech recognition

technology to detect pronunciation errors and provide corrective feedback. Examples include

apps like ELSA Speak, Google’s Read Along, and Microsoft’s Immersive Reader. AI can also

compare learner speech to native speaker models, visualize phoneme articulation, and deliver

instant recommendations for improvement.

Benefits of AI-Powered Feedback

AI-powered feedback systems offer several pedagogical advantages. First, they provide

immediate, consistent feedback without the need for teacher intervention. This autonomy

encourages learners to practice more frequently. Second, AI can detect subtle phonetic errors

and offer customized guidance, which is difficult for most human instructors to provide

consistently. Third, learners gain increased confidence as they receive real-time performance

analytics and progress tracking.

Drawbacks and Challenges


background image

INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE

ISSN: 2692-5206, Impact Factor: 12,23

American Academic publishers, volume 05, issue 06,2025

Journal:

https://www.academicpublishers.org/journals/index.php/ijai

page 1546

Despite its benefits, AI-based pronunciation training has notable limitations. AI systems may

struggle with diverse accents and speech patterns, leading to inaccurate feedback. There are

also concerns regarding over-reliance on technology, which can reduce human interaction and

communicative authenticity. Moreover, limited access to high-quality devices and reliable

internet hinders equitable implementation, especially in low-resource settings.

Case Studies and Evidence

A 2022 study by Garcia & Lin found that students using AI pronunciation apps improved their

speaking scores by 27% compared to traditional methods. Another study conducted by Lee et al.

(2021) highlighted how AI feedback improved phoneme accuracy and learner motivation in

Korean EFL contexts. However, in both studies, teacher facilitation remained crucial to help

students interpret and apply AI-generated feedback effectively.

Recommendations for Implementation

Educators should adopt a blended approach where AI tools supplement rather than replace

traditional instruction. Teachers must be trained to interpret AI feedback and guide learners

accordingly. Curriculum developers should ensure AI tools are aligned with communicative

language teaching principles and promote meaningful oral interactions.

Conclusion

AI-powered feedback systems hold great promise for advancing speaking and pronunciation

instruction in English language teaching. They provide timely, personalized support and

enhance learner autonomy. However, to maximize their effectiveness, these tools must be

integrated thoughtfully, supported by trained teachers, and adapted to diverse learner contexts.

References:

Garcia, M., & Lin, Y. (2022). AI and Pronunciation: A New Path in Language Instruction.

Journal of Educational Technology, 45(2), 134–149.

Lee, J., Kim, S., & Park, H. (2021). Speech Recognition Feedback in EFL Pronunciation

Learning. TESOL Quarterly, 55(3), 487–506.

Warschauer, M., & Grimes, D. (2020). Automated Feedback and Second Language Speaking.

Language Learning & Technology, 24(1), 78–92.

Yang, S. (2019). Pronunciation Technology and Second Language Acquisition. Computer-

Assisted Language Learning, 32(5–6), 590–611.

References

Garcia, M., & Lin, Y. (2022). AI and Pronunciation: A New Path in Language Instruction. Journal of Educational Technology, 45(2), 134–149.

Lee, J., Kim, S., & Park, H. (2021). Speech Recognition Feedback in EFL Pronunciation Learning. TESOL Quarterly, 55(3), 487–506.

Warschauer, M., & Grimes, D. (2020). Automated Feedback and Second Language Speaking. Language Learning & Technology, 24(1), 78–92.

Yang, S. (2019). Pronunciation Technology and Second Language Acquisition. Computer-Assisted Language Learning, 32(5–6), 590–611.