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June 14, 2026Kocaeli Journal of Science and EngineeringOpen Access

Detection of Pronunciation Errors in Arabic Sentences Using LLM with Voice-Based Transformer Models

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Authors

ŞÇŞükrü Selim ÇalıkZKZeynep Hilal KilimciAKAyhan Küçükmanіşa

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Overview

Randomized trial evaluates pronunciation accuracy in Arabic Qur'an recitation, suggesting improvements in language technology applications.

Key Points

  • The study aims to evaluate the pronunciation accuracy of Qur'an recitation using automated methods.
  • Audio recordings from ten hafiz reading the Qur'an aloud were collected.
  • Speech-to-text models were used to convert audio data into text.
  • Similarity metrics were employed to compare generated texts with reference Qur'an texts.
  • High accuracy in detecting pronunciation errors in recited Qur'an texts.
  • Utilization of voice-based transformer models enhanced the evaluation process.
  • The system presents a viable tool for improving educational practices in religious contexts.

Cite This Study

Çalık et al. (2026) studied this question.

synapsesocial.com/papers/6a2e4753b1cc60ccdea8bd02https://doi.org/10.34088/kojose.1867692
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