Verification System for Quran Recitation Recordings

2010 5th Cairo International Biomedical Engineering Conference, 2010

This paper describes an automatic system for the detection of some common pronunciation mistakes occurring in Quran recitation. It addresses the application of the Arabic language pronunciation rules. The system is a basic step towards a complete automatic teaching system of the Holy Quran recitation rules. The focus of this study is to detect the non proper pronunciation of a chosen set of emphatic and non-emphatic uttered letters. To achieve this goal, first we have developed several algorithms to extract the discriminating feature from specific uttered words that include the letters of interest. Then we developed a new semi automatic approach for segmentation of the considered speech to extract the target sounds. The reference in this study is the well recognized recitation rules of the Holy Quran. A database of correct readings for the chosen uttered letters was recorded from six famous referenced readers to be the control set of our system. The experiments are applied to test the pronunciation accuracy of the system users. The results showed the success of the system by 100% for the samples taken to detect the correct pronunciations and most common predictable mistakes.

Tajweed is a set of rules to read the Quran in a correct Pronunciation of the letters with all its Qualities, while Reciting the Quran. which means you have to give every letter in the Quran its due of characteristics and apply it to this particular letter in this specific situation while reading, which may differ in other times. These characteristics include melodic rules, like where to stop and for how long, when to merge two letters in pronunciation or when to stretch some, or even when to put more strength on some letters over other. Most of the papers focus mainly on the main recitation rules and the pronunciation but not (Ahkam AL Tajweed) which give different rhythm and different melody to the pronunciation with every different rule of (Tajweed). Which is also considered very important and essential in Reading the Quran as it can give different meanings to the words. In this paper we discuss in detail full system for automatic recognition of Quran Recitation Rules (Tajweed) by using support vector machine and threshold scoring system.

IOP Conference Series: Materials Science and Engineering

Memorizing Holy Quran or Tahfidz is important to worship for Muslim around the world. This research proposed a solution in memorizing and learning Holy Quran easily. To help in remembering the sentence of Holy Quran, Fisher-Yates Shuffle had implemented for randomization of the letter of the Holy Quran. In this research, the sound of Holy Quran had recorded and it was converted into Arabic text to recognize the character of text. Jaro-Winkler was used for text matching algorithm, and Google Speech API help to define speech recognition. The result showed that Fisher-Yates Shuffle Algorithm was successfully applied in randomization with 15 times of experiments. And also, Jaro-Winkler Distance algorithm had performed well as text matching between text from speech recognition and Holy Quran text. The result showed that the percentage of accuracy was around 91% and an average of matching time was 1.9 ms.

Robust Speech Recognition and …

International Journal of …, 2008

Each person's voice is different. Thus, the Quran sound, which had been recited by most of recitors will probably tend to differ a lot from one person to another. Although those Quranic sentence were particularly taken from the same verse, but the way of the sentence in Al-Quran been recited or delivered may be different. It may produce the difference sounds for the different recitors. Those same combinations of letters may be pronounced differently due to the use of harakates. This paper seeks to provide a comprehensive review of Quran Arabic verse recitation recognition focusing on the techniques used, the advantages, and drawbacks. Areas with potential of further expansion are identified for future research for support in j-QAF learning.

International Journal of Advanced Trends in Computer Science and Engineering

The main objective of the research is to develop the correction-mapping model for Al-Quran recitation performance evaluation engine. Machine learning and Digital Signal Processing techniques are applied in representing and analyzing the recitation speech signal. Consequently, a form of recitation correction results is derived and formulated for the final performance evaluation. The proposed corrective mapping model demonstrated in this paper confronted, but not limited to, with the challenging issues of variability of speaker recitation, recitation representation, speaker adaptation, feature extraction, parameters estimation and threshold process classification. The experimental results concluded the Al-Quran automated correction system knowns as Intelligent Quran Recitation Assistant (nur-IQRA) will be able to fulfil the current and future trends of digital society.

Apps is one of the latest technologies for dakwah. It is a valuable tool that supports the dakwah process with better personalization, ubiquitous environment and offers a faster service than web sites. The main objective of this research is to develop the model for technology application in the chosen Islam book (Al-Quran Kitab) recitation evaluation. Here, the scientific approaches are applied in analysing the recitation speech and correcting the recitation based on recitation rules. It will convert the conventional to technology assist approaches on Al-Quran recitation. Commonly, a Muslim who wants to recite the Al Quran should learn the correct technique of reciting the Al-Quran. The uniqueness of Al-Quran reading (recitation) approach is related to the speech properties and recitation regulation. It must be considered in speech recognition practice to reveal the incorrectness of recitation. The technology concerned must confront with the challenging issues of features representation and classification based on digital speech processing (DSP) techniques to automatically identify, classify and recognize the speech of Al-Quran recitation for the function of representation and corrective tasking for recitation rules. An intelligent system for the automatic recitation correction system is highly concerned. An automatic recitation correction system of Al-Quran is a very challenging task in term of self-correction indication and robust matching approach. The development of an intelligent automatic correction model can support the Muslim to perform correctly Al Quran recitation.

International Journal of Advanced Computer Science and Applications

The use of technological speech recognition systems with a variety of approaches and techniques has grown rapidly in a variety of human-machine interaction applications. Further to this, a computerized assessment system to identify errors in reading the Qur'an can be developed to practice the advantages of technology that exist today. Based on Quranic syllable utterances, which contain Tajweed rules that generally consist of Makhraj (articulation process), Sifaat (letter features or pronunciation) and Harakat (pronunciation extension), this paper attempts to present the technological capabilities in realizing Quranic recitation assessment. The transformation of the digital signal of the Quranic voice with the identification of reading errors (based on the Law of Tajweed) is the main focus of this paper. This involves many stages in the process related to the representation of Quranic syllable-based Recitation Speech Signal (QRSS), feature extraction, non-phonetic transcription Quranic Recitation Acoustic Model (QRAM), and threshold classification processes. MFCC-Formants are used in a miniature state that are hybridized with three bands in representing QRSS combined vowels and consonants. A human-guided threshold classification approach is used to assess recitation based on Quranic syllables and threshold classification performance for the low, medium, and high band groups with performances of 87.27%, 86.86%and 86.33%, respectively.

2015

Speech processing has been the subject of an extensive number of research studies. Speech synthesis is the process of transferring text to speech. Phonetic transcription represents an essential part of any text-to-speech system. This paper proposes a transcription technique dedicated for the Quranic text. Transcribing Quranic text is a challenging problem as some letters have different phonemes for the same letter, depending on its neighbors. Different rules are proposed to handle the problem of Quranic text transcription depending on the art of Intonation (Tajweed). In addition, a rule based syllabification technique is presented. This research will have a good impact in the service of Holy Quran and its science. This research work is important to implement Quran recitation synthesis prototype as it addresses Quranic text transcription and syllabification. Quran recitation synthesis has main motivation of reducing space of Quranic sound files.

E-Learning - Engineering, On-Job Training and Interactive Teaching, 2012

Evolution in Electrical and Electronic Engineering, 2021

Quran is learned at the early stage of Muslim children and usually taught by the religious teachers. It must be recited with precise and correct tajweed in order to avoid the misunderstanding of its meaning. Sometimes the children recite Quran without the presence of the teacher which the children tend to recite Quran wrongly since there is no guidance. Besides, different children have different learning style since some are visual learners and others are audio learners. In order to help the children to learn Quran in an attractive way, an Automated Tajweed Checking System for Children in Learning Quran is proposed. This system not intended to replace the role of the teachers but to attract the children in learning Quran and help the children to learn Quran without the presence of the teachers. The method of the project uses the concept of voice recognition. In voice recognition there are a few steps involve which are pre-processing, feature extraction, feature classification and recognition. The feature extraction technique used is Mel-Frequency Cepstral Coefficient (MFCC) while for feature classification and recognition technique used is Hidden Markov Model (HMM). This proposed system is believed to recognize recitation efficiently, thus helping children in learning Quran once completed.

Revue d'intelligence artificielle, 2022

The Speaker identification process is not a new trend; however, for the Arabic Holy Quran recitation, there are still quite improvements that can make this process more accurate and reliable. This paper collected the input data from 14 native Arabic reciters, consisting of "Surah Al-Kawthar" speech signals from the Holy Quran. Moreover, this paper discusses the accuracy rates for 8 and 16 features. Indeed, a modified Vector Quantization (VQ) technique will be presented, in addition to realistically matching the centroids of the various codebooks and measuring systems' effectiveness. Note that the VQ technique will be utilized to generate the codebooks by clustering these features into a finite number of centroids. The proposed system's software was built and executed using MATLAB®. The proposed system's total accuracy rate was 97.92% and 98.51% for 8 and 16 centroids codebooks, respectively. However, this study discussed two validation tactics to ensure that the outcomes are reliable and can be reproduced. Hence, the K-mean clustering algorithm has been used to validate the obtained results and discuss the outcomes of this study. Finally, it has been found that the improved VQ method gives a better result than the Kmeans method.

Electronics

Phoneme classification performance is a critical factor for the successful implementation of a speech recognition system. A mispronunciation of Arabic short vowels or long vowels can change the meaning of a complete sentence. However, correctly distinguishing phonemes with vowels in Quranic recitation (the Holy book of Muslims) is still a challenging problem even for state-of-the-art classification methods, where the duration of the phonemes is considered one of the important features in Quranic recitation, which is called Medd, which means that the phoneme lengthening is governed by strict rules. These features of recitation call for an additional classification of phonemes in Qur’anic recitation due to that the phonemes classification based on Arabic language characteristics is insufficient to recognize Tajweed rules, including the rules of Medd. This paper introduces a Rule-Based Phoneme Duration Algorithm to improve phoneme classification in Qur’anic recitation. The phonemes of ...

International Journal of Advanced Computer Science and Applications, 2011

In this paper we describe the process of designing a task-oriented continuous speech recognition system for Arabic, based on CMU Sphinx4, to be used in the voice interface of Quranic reader. The concept of the Quranic reader controlled by speech is presented, the collection of the corpus and creation of acoustic model are described in detail taking into account a specificities of Arabic language and the desired application.

International Journal of Computer Science and Mobile Computing, 2021

This paper provides a literature survey about Automatic Speech Recognition (ASR) systems for learning Arabic language and Al-Quran Recitation. The growth in communication technologies and AI (specially Machine learning and Deep learning) led researchers in ASR field to thinking of and developing ASR systems which mimic humans in their understand of natural speech and recognition. One of the most important applications in ASR is natural language processing (NLP). Arabic language is one of these languages. ASR systems which developed for Arabic language help Arabs and non-Arabs in learning Arabic language and so Al-Quran recitation and memorization in proper way according to recitation rules (Tajweed). This paper concentrate on ASR systems in general, challenges, PROS, CONS, Arabic language ASR systems and challenges faced them and finally Al-Quran recitation verification systems.