QVR: Quranic Verses Recitation Recognition System using PocketSphinx

Abstract

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 so-called the Quranic Verse Recitation Recognition (QVR) system using PocketSphinx to convert the Quranic verse from Arabic sound to Roman text and determine the accuracy of reciters, has been developed. 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 via Quran Roman text. 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.

Visual Lip-Reading for Quranic Arabic Alphabets and Words Using Deep Learning

“…In recent decades, researchers have presented many studies related to the Holy Quran, which are concerned with helping to learn and recite the Holy Quran correctly [27][28][29]. The researchers were also interested in several studies in the field of the seven readings recognition (Qiraat) and distinguishing it, such as in [27,30].…”