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

The continuing advances in deep learning have paved the way for several challenging ideas.One such idea is visual lip-reading,which has recently drawn many research interests.Lip-reading,often referred to as visual speech recognition,is the ability to understand and predict spoken speech based solely on lip movements without using sounds.Due to the lack of research studies on visual speech recognition for the Arabic language in general,and its absence in the Quranic research,this research aims to fill this gap.This paper introduces a new publicly available Arabic lip-reading dataset containing 10490 videos captured from multiple viewpoints and comprising data samples at the letter level(i.e.,single letters(single alphabets)and Quranic disjoined letters)and in the word level based on the content and context of the book Al-Qaida Al-Noorania.This research uses visual speech recognition to recognize spoken Arabic letters(Arabic alphabets),Quranic disjoined letters,and Quranic words,mainly phonetic as they are recited in the Holy Quran according to Quranic study aid entitled Al-Qaida Al-Noorania.This study could further validate the correctness of pronunciation and,subsequently,assist people in correctly reciting Quran.Furthermore,a detailed description of the created dataset and its construction methodology is provided.This new dataset is used to train an effective pre-trained deep learning CNN model throughout transfer learning for lip-reading,achieving the accuracies of 83.3%,80.5%,and 77.5%on words,disjoined letters,and single letters,respectively,where an extended analysis of the results is provided.Finally,the experimental outcomes,different research aspects,and dataset collection consistency and challenges are discussed and concluded with several new promising trends for future work.

Tamper Detection and Localization for Quranic Text Watermarking Scheme Based on Hybrid Technique

The text of the Quran is principally dependent on the Arabic language.Therefore,improving the security and reliability of the Quran’s text when it is exchanged via internet networks has become one of the most difcult challenges that researchers face today.Consequently,the diacritical marks in the Holy Quran which represent Arabic vowels(i,j.s)known as the kashida(or“extended letters”)must be protected from changes.The cover text of the Quran and its watermarked text are different due to the low values of the Peak Signal to Noise Ratio(PSNR),and Normalized Cross-Correlation(NCC);thus,the location for tamper detection accuracy is low.The gap addressed in this paper to improve the security of Arabic text in the Holy Quran by using vowels with kashida.To enhance the watermarking scheme of the text of the Quran based on hybrid techniques(XOR and queuing techniques)of the purposed scheme.The methodology propose scheme consists of four phases:The rst phase is pre-processing.This is followed by the second phase where an embedding process takes place to hide the data after the vowel letters wherein if the secret bit is“1”,it inserts the kashida but does not insert the kashida if the bit is“0”.The third phase is an extraction process and the last phase is to evaluate the performance of the proposed scheme by using PSNR(for the imperceptibility),and NCC(for the security of the watermarking).Experiments were performed on three datasets of varying lengths under multiple random locations of insertion,reorder and deletion attacks.The experimental results were revealed the improvement of the NCC by 1.76%,PSNR by 9.6%compared to available current schemes.

Quranic Script Optical Text Recognition Using Deep Learning in IoT Systems

Since the worldwide spread of internet-connected devices and rapid advances made in Internet of Things(IoT)systems,much research has been done in using machine learning methods to recognize IoT sensors data.This is particularly the case for optical character recognition of handwritten scripts.Recognizing text in images has several useful applications,including content-based image retrieval,searching and document archiving.The Arabic language is one of the mostly used tongues in the world.However,Arabic text recognition in imagery is still very much in the nascent stage,especially handwritten text.This is mainly due to the language complexities,different writing styles,variations in the shape of characters,diacritics,and connected nature of Arabic text.In this paper,two deep learning models were proposed.The first model was based on a sequence-to-sequence recognition,while the second model was based on a fully convolution network.To measure the performance of these models,a new dataset,called QTID(Quran Text Image Dataset)was devised.This is the first Arabic dataset that includes Arabic diacritics.It consists of 309,720 different 192×64 annotated Arabic word images,which comprise 2,494,428 characters in total taken from the Holy Quran.The annotated images in the dataset were randomly divided into 90%,5%,and 5%sets for training,validation,and testing purposes,respectively.Both models were set up to recognize the Arabic Othmani font in the QTID.Experimental results show that the proposed methods achieve state-of-the-art outcomes.Furthermore,the proposed models surpass expectations in terms of character recognition rate,F1-score,average precision,and recall values.They are superior to the best Arabic text recognition engines like Tesseract and ABBYY FineReader.

Quran memorisation and heart rate variability:How do they correlate?

BACKGROUND Heart rate variability(HRV)was shown to be affected by performing religious activities.AIM To examine the relationship between the level of Quran(the holy book of Muslims)memorisation and HRV among teenagers.METHODS This experimental study included 16 Tahfiz students and 16 non-Tahfiz students(n=32).The HRV was measured in three tasks:Recalling familiar verses,memorising new verses,and recalling the newly memorised verses of the Quran.HRV analysis was done using these parameters:Standard deviation of N-N(heartbeat peak)interval;low frequency(LF);high frequency(HF)and LF/HF ratio.RESULTS There were significant differences between tasks for all parameters(P<0.05).However,between the groups,only the LF/HF ratio had significant differences,with F=5.04,P<0.05.Pearson correlation showed a moderate positive correlation between the number of pages memorised and the LF/HF ratio(r=0.61,P<0.05).CONCLUSION Quran memorisation increased the HRV and our results suggested that this activity could be developed as an effective sympathovagal modulation training activity.

Virtual Learning System (Miqra’ah) for Quran Recitations for Sighted and Blind Students

Quran has ten famous recitations and twenty different narrations. It is well known that the best way is to learn from qualified and authentic scientists (Sheikh's) in one or more of these narrations. Due to 1) the widespread of the Internet and the ease of use and availability of computers and the smart phones that enables access to the Internet;2) the business of people hindering them to attend physical learning environments;and 3) the very few number of elder licensed scientists, we have developed a virtual learning system (Electronic Miqra’ah). Scientists can supervise remotely the registered students. Students (from different ages) can register from anywhere in the world given that they have Internet connection. Students can interact with the scientist in real time so that they can help them memorize (Tahfeez), guide them for error correction, and give them lectures or lessons through virtual learning rooms. The targeted groups of users can be nonblind people, blind people, manual-disabled people and illiterate people. We have developed this system such that it takes the commands via voice in addition to the normal inputs like mouse and keyboard. Users can dictate the commands to the system orally and the system recognizes the spoken phrases and executes them. We have developed an efficient speech recognition engine that is speaker independent and accent independent. The system administrators create several virtual learning rooms and register the licensed scientists. Administrators prepare a daily schedule for each room. Students can register to any of these rooms by pronouncing its name. Each student is allocated a portion of time where he/she can interact directly by voice with the scientist. Other students can listen to the current student’s recitation and the error corrections, guidance or lessons from the scientists.

Payload Capacity Scheme for Quran Text Watermarking Based on Vowels with Kashida

The most sensitive Arabic text available online is the digital Holy Quran.This sacred Islamic religious book is recited by all Muslims worldwide including non-Arabs as part of their worship needs.Thus,it should be protected from any kind of tampering to keep its invaluable meaning intact.Different characteristics of Arabic letters like the vowels(),Kashida(extended letters),and other symbols in the Holy Quran must be secured from alterations.The cover text of the Quran and its watermarked text are different due to the low values of the Peak Signal to Noise Ratio(PSNR)and Embedding Ratio(ER).A watermarking technique with enhanced attributes must,therefore,be designed for the Quran’s text using Arabic vowels with kashida.The gap addressed by this paper is to improve the security of Arabic text in the Holy Quran by using vowels with kashida.The purpose of this paper is to enhance the Quran text watermarking scheme based on a reversing technique.The methodology consists of four phases:The first phase is a pre-processing followed by the second phase-the embedding process phase—which will hide the data after the vowels.That is,if the secret bit is“1”,then the kashida is inserted;however,the kashida is not inserted if the bit is“0”.The third phase is the extraction process and the last phase is to evaluate the performance of the proposed scheme by using PSNR(for the imperceptibility)and ER(for the capacity).The experimental results show that the proposed method of imperceptibility insertion is also optimized with the help of a reversing algorithm.The proposed strategy obtains a 90.5%capacity.Furthermore,the proposed algorithm attained 66.1%which is referred to as imperceptibility.

Twentieth Century Wanzams among the Asante People of Ghana: A Historical Study of the Facts on Male Circumcision

This paper studies the history of circumcision amongst religious and traditional societies and the arguments on the medical or non-medical essence of the practice. The paper further highlights amongst the Asante people of Ghana, a practice argued to have been introduced by Islamic Wanzams who are severally referred to as Muslim Circumcision Surgeons. Often circumcision amongst communities in West, Southern Africa, Asia and other Aboriginal groups has been spurred on by customs and traditions [1]. Yet the case of Asante was different. Hence attention has been paid to the history of circumcision amongst the people of Asante. More significantly, the health implications associated with circumcision surgery in Asante have been highlighted. Possible benefits from the practice of circumcision and the potential dangers associated with it, especially the operations of the Asante circumcision surgeons (Wanzams) have been amply scrutinised in the narrative. In the conclusion, attention is paid to some of the scientific arguments for male circumcision. The study is purely qualitative relying on documentary and non-documentary sources. Some of the documentary sources have been gleaned from journal articles, news papers and books etc. The non-documentary data have been sourced from interviews. Both the documentary and non-documentary sources have been thematically pieced together to form a social history of medicine narrative which has potential ramifications on the essence of male circumcision by Wanzams, as well as the need for further research, training and dialogue in the practice in Ghana and Asante in particular.

Economic Counseling Psychology for Management Economic Crisis

In the economic world of the economic class down there are some challenges in economic life that is the ability to survive in a mediocre economy,defend themselves against the work they have lived so far,mental reinforcement when unable to buy anything,self-surrender to the economic destiny they endured.is the economic counseling of the Quran,is one of the approaches given to the poor who face problems such as removing"I'm confused,I want to kill myself,just die if I keep this up".Through the verses of the Koran given to the poor primarily,being able to reduce the mental pressure of suicidal ideation and build resilience in the face of life's problems.

Understanding Hidden Meanings of Quran’s Words Using Mobile/Android Application

With technology getting to the next level, many resources cannot only educate our children and youth, but also let them know what our religion is all about. The idea is to educate and make our children aware, but in a way that makes them happy and suits the cause. Designing an application, which let users know about various verses and words of Holy Quran in easy way, is very important. This study helps children to relate all those words with real life, reel life and later then will recognize them easily. The illustration in this study plays a key role to do the research in a right way. In this paper, the application can do a lot of experiment with puzzle and other random applications. Moreover, that application gives children an opportunity to use their brain in order to recognize, the Quranic words in an innovative way, which will serve them in the knowledge about the Holy Quran. From our experiential results around 50% of Children using this application for our dataset were satisfied with the application.

Educational System for the Holy Quran and Its Sciences for Blind and Handicapped People Based on Google Speech API

There is a great need to provide educational environments for blind and handicapped people. There are many Islamic websites and applications dedicated to the educational services for the Holy Quran and Its Sciences (Quran Recitations, the interpretations, etc.) on the Internet. Unfortunately, blind and handicapped people could not use these services. These people cannot use the keyboard and the mouse. In addition, the ability to read and write is essential to benefit from these services. In this paper, we present an educational environment that allows these people to take full advantage of the scientific materials. This is done through the interaction with the system using voice commands by speaking directly without the need to write or to use the mouse. Google Speech API is used for the universal speech recognition after a preprocessing and post processing phases to improve the accuracy. For blind people, responses of these commands will be played back through the audio device instead of displaying the text to the screen. The text will be displayed on the screen to help other people make use of the system.

Simple and Multi Linear Regression Model of Verbs in Quran

This paper mainly presented a good simple and multi-linear regression model of verbs in the Quran book. This model, gives an analysis for the influence to frequency of words with the form (—un, ---) made by the frequency of plural present verbs (t—un, ---) or (y—un, ---), and models, and the relationship between independent variables and dependent variable by fitting a linear equation to the observed data with simple linear regression model. The matlab function is used for finding the parameters of the linear regression model and plotting the fits. The results show that the parameters of the model are one vector (1, 1) and mean of dataset is (6, 7). Its corresponding to the verb with input is frequency of the verb they enter and the frequency of enter (yadkolun ?dakilun), also other 17 points exist in the line and in the dataset of 387 verbs and their derivate verbs in Quran. The name of Allah () showed when we use tree variables and plot it in 3D with option “Show Text” for a multi regression model.