QVR: Quranic Verses Recitation Recognition System Using PocketSphinx


  • Hasan Ali Gamal Al-Kaf Universiti Teknologi PETRONAS
  • Muhammad Suhaimi Sulong Universiti Tun Hussein Onn Malaysia
  • Ariffuddin Joret Universiti Tun Hussein Onn Malaysia
  • Nuramin Fitri Aminuddin Universiti Tun Hussein Onn Malaysia
  • Che Adenan Mohammad Universiti Tun Hussein Onn Malaysia


Quran verse, PocketSphinx, automatic speech recognition


The recitation of Quran verses according to the actual tajweed is obligatory and it must be accurate and precise in pronunciation. Hence, it should always be reviewed by an expert on the recitation of the Quran. Through the latest technology, this recitation review can be implemented through an application system and it is most appropriate in this current Covid-19 pandemic situation where system application online is deemed to be developed. In this empirical study, a recognition system using PocketSphinx to convert the Quranic verse from sound to text, and determine the accuracy of reciters has been developed so-called the Quranic Verse Recitation Recognition (QVR) system. The Graphical User Interface (GUI) of the system with a user-friendly environment was designed using Microsoft Visual Basic 6 in an Ubuntu platform. A verse of surah al-Ikhlas has been chosen in this study and the data were collected by recording 855 audios as training data recorded by professional reciters. Another 105 audios were collected as testing data, to test the accuracy of the system. The results indicate that the system obtained a 100% accuracy with a 0.00% of word error rate (WER) for both training and testing data of the said audios. The system with automatic speech recognition (ASR) engine system demonstrates that it has been successfully designed and developed, and is significant to be extended further. Added, it will be improved with the addition of other Quran surahs.




How to Cite

Al-Kaf, H. A. G., Sulong, M. S., Joret, A. ., Aminuddin, N. F. ., & Mohammad, C. A. . (2021). QVR: Quranic Verses Recitation Recognition System Using PocketSphinx. Journal of Quranic Sciences and Research, 2(2), 35–41. Retrieved from https://publisher.uthm.edu.my/ojs/index.php/jqsr/article/view/9760