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Intelligent Quran Recitation Recognition and Verification: Research Trends and Open Issues

  • Research Article-Computer Engineering and Computer Science
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Abstract

Muslims aim to recite and memorize the Holy Quran correctly. However, traditional recitation verification approaches depend on humans who may not be available. On the other hand, Artificial Intelligence (AI) capabilities assist in developing intelligent recitation verification tools based on speech recognition techniques. This study aims to overview the current state of the intelligent Quran recitation recognition and verification solutions and highlight the related open issues. A systematic literature review was performed on the published paper since 2006 up to date to answer six research questions. The research questions covered the speech recognition techniques and methods used to develop Quran recitation recognition and verification models, the database and tools used, and the existing mobile application supporting real-time intelligent Quran recitation verification services. Based on the review results, a taxonomy of the Quran recitation recognition and verification techniques was generated, including traditional and end-to-end speech recognition methods. Moreover, the limitations of the existing AI-based Quran recitation verification applications were reported. Additionally, the available Quran audio datasets and tools capable of dealing with Quranic speech were identified. In conclusion, several open issues can be addressed in future research, e.g., considering AI-based approaches to ensure sequence recitation and recognize diacritics-based errors.

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Data Availability

Not applicable.

Code Availability

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Notes

  1. The Holy Quran.

Abbreviations

Diacritics:

Marks are placed above or under a letter in Arabic words, indicating a particular pronunciation and meaning.

Ghunnah:

Nasalization.

Idgham:

A recitation rule combines the Noon As-Sakenah or the Tanween with the following Idgham letter. There are six Idgham letters, which are Yaa, Raa, Meem, Lam, Noon, and Waw (ي، ر، م، ل، ن، و)

Idhar:

A recitation rule focuses on clearly pronouncing letters from their Makharej, without changes. There are six Idhar letters, which are Alef, Ha, Kha, Aen, Ghain, and Haa (أ، ح، خ، ع، غ، هـ)

Ikhfa:

A recitation rule conceals part of the pronounced letter whenever Tanween or Noon As-Sakenah is found before the Ikhfa letter. Thus, the word will be pronounced between Idhar and Idgham. There are 15 Ikhfa letters, which are the remaining Arabic letters after extracting the Idhar, Iqlab, and Idgham letters.

Iqlab:

A recitation rule switches the pronunciation of Noon As-Sakenah or Tanween to Meem when the letter Baa was found after them.

Madd:

Recitation rules that extend the sound of the Madd letter. There are three Madd letters, which are Alef, Yaa, Waw (ا، ي، و)

Makharej:

Articulation.

Quran:

The holy book for Muslims that guides their living and discusses many life and religious aspects, consisting of 114 chapters. The Quran was revealed and written in Arabic.

Quran Chapter:

A Quran chapter consists of a number of verses.

Quran Section:

A Quran section consists of a number of chapters.

Quran verse:

A sentence placed between Quranic numbering symbols. Quran verses have different lengths.

Recitation Correction:

The process of correcting the reciter’s recitation during a recitation session whenever a recitation mistake was encountered to ensure correct recitation.

Recitation Type:

The way the Quran is being recited affects some pronunciations and Tajweed rules. There are seven recitation types of the Quran, such as Hafs and Warsh.

Recitation Verification:

The process of verifying and assessing the reciter’s recitation during a recitation session and reporting the recitation errors.

Reciter:

The person who recites the Quran. This person could be an expert or an ordinary reciter.

Tafkheem:

The act of fattening the pronunciation of a letter in certain conditions.

Tajweed:

Recitation rules. The way of Quran recitation where the reciter follows a set of rules for correct and perfect recitation.

Tanween:

The added “n” sound to the end of the word.

Tarqeeq:

The act of thinning the pronunciation of a letter in certain conditions.

Tarteel:

The act of reciting the Quran with spiritual focus results in understanding the verses’ meanings and linking them with each other.

AI:

Artificial Intelligence

BLSTM:

Bidirectional Long Short-Term Memory

CDBN:

Convolutional Deep Belief Network

CMU:

Carnegie Mellon University

CNN:

Convolutional Neural Network

CTC:

Connectionist Temporal Classification

DCT:

Discrete Cosine Transform

GMM:

Gaussian Mixture Model

HMM:

Hidden Markov Model

HMM-BLSTM:

Hidden Markov Model-Bidirectional Long Short-Term Memory

HMM-GMM:

Hidden Markov Model-Gaussian Mixture Model

HMM-SPL:

Hidden Markov Model-based Spectral Peak Location

iOS:

iPhone Operation System

JSGF:

Java Speech Grammar Format

LDA:

Linear Discriminate Analysis

LPC:

Linear Predictive Coding

LSTM:

Long Short-Term Memory

MaLSTM :

Manhattan distance-based LSTM

MFCCs:

Mel-Frequency Cepstral Coefficients

MFSCs:

Mel-Frequency Spectral Coefficients

ML :

Machine Learning

MLLR:

Maximum Likelihood Linear Regression

MLLT:

Maximum Likelihood Linear Transform

PLP:

Perceptual Linear Prediction

RNN:

Recurrent Neural Network

RQ:

Research Question

Siamese-LSTM:

Siamese- Long Short-Term Memory

SLR :

Systematic Literature Review

STFT:

Short Time Fourier Transform

SVM:

Support Vector Machine

TDNN:

Time Delay Neural Networks

VQ :

Vector Quantization

WEKA:

Waikato Environment for Knowledge Analysis

WER:

Word Error Rate

WPD:

Wavelet Packet Decomposition

WoS:

Web of Science

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  1. Department of Information Technology, College of Computer, Qassim University, Buraydah, 51452, Saudi Arabia

    Sarah S. Alrumiah & Amal A. Al-Shargabi

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Alrumiah, S.S., Al-Shargabi, A.A. Intelligent Quran Recitation Recognition and Verification: Research Trends and Open Issues. Arab J Sci Eng 48, 9859–9885 (2023). https://doi.org/10.1007/s13369-022-07273-8

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