Phoneme-Based Recognizer to Assist Reading the Holy Quran

Elhadj, Yahya O. Mohamed; Alghamdi, Mohammed H.; Alkanhal, Mohamed

doi:10.1007/978-3-319-01778-5_15

Cited by 11 publications

(6 citation statements)

References 3 publications

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“…Single acoustic model has been considered for geminated and nongeminated consonant sounds. This is in accordance with the findings mentioned in [9] as well as the initial experiments conducted before finalizing, whether to include separate acoustic models for geminated sounds or not. To introduce a geminated consonant in reference transcriptions, respective phoneme was placed twice.…”

Section: Grammarsupporting

confidence: 92%

“…Comparing the extent of work in the domain of Classical Arabic, we found that MSA remains the focus of speech scientists mostly. Recently some contribution has been made in making computers, learn to recognize Holy Quran at phoneme and allophone levels [9,47]. As all reciters followed 'Tajwid' rules in recitation, it implies to keep same phoneme-level transcription for all reciters.…”

Section: Data Preparationmentioning

confidence: 99%

“…Also it does not accommodate non-native Arab speakers. In another paper [9], phoneme-based speaker dependent recognizer of THQ recitation is proposed. Acoustic models are trained on the 30th part of THQ and are based on ML approach.…”

Section: Classical Arabic Asrsmentioning

confidence: 99%

See 2 more Smart Citations

Discriminative Training for Phonetic Recognition of the Holy Quran

2015

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This paper presents the development of Holy Quran recitation recognizer. The decoder of recognizer performs sub-word level recognition at phoneme. The paper demonstrates high recognition accuracies achieved by applying incremental refinements to the HMM models of the phonemes during the training stage. The Maximumlikelihood (ML) criterion is first applied for HMMs parameter estimation, which produces average recognition accuracies of up to 83 %. This is followed by discriminative technique of minimum phone error (MPE), which is applied to minimize recognition error at phoneme level. Investigation shows that MPE based acoustic models improve generalization. The results show 3-4 % improvement in recognition accuracies, which are promising when compared with the case of ML approach applied alone.

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Section: Grammarsupporting

confidence: 92%

Section: Data Preparationmentioning

confidence: 99%

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Discriminative Training for Phonetic Recognition of the Holy Quran

2015

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“…As findings of a previously funded research project [7], two baseline HMM-based systems for phonemes and allophones [8,9] were constructed using the mentioned speech database. The number of allophones in the speech database is 110 plus a silence unit which is counted as normal allophone indicating short pauses during the recitations, while the number of phonemes is 60, which represents almost half of the number of allophones.…”

Section: Research Efforts Summarymentioning

confidence: 99%

Helpful Statistics in Recognizing Basic Arabic Phonemes

Khelifa¹,

Yousfi²,

Elhadj³

et al. 2017

ijacsa

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Abstract-The recognition of continuous speech is one of the main challenges in the building of automatic speech recognition (ASR) systems, especially when it comes to phonetically complex languages such as Arabic. An ASR system seems to be actually in a blocked alley. Nearly all solutions follow the same general model. The previous research focused on enhancing its performance by incorporating supplementary features. This paper is part of ongoing research efforts aimed at developing a high-performance Arabic speech recognition system for learning and teaching purposes. It investigates a statistical analysis of certain distinctive features of the basic Arabic phonemes which seems helpful in enhancing the performance of a baseline HMMbased ASR system. The statistics are collected using a particular Arabic speech database, which involves ten different male speakers and more than eight hours of speech which covers all Arabic phonemes. In HMM modeling framework, the statistics provided are helpful in establishing the appropriate number of HMM states for each phoneme and they can also be utilized as an initial condition for the EM estimation procedure, which generally, accelerates the estimation process and, thus, improves the performance of the system. The obtained findings are presented and possible applications of automatic speech recognition and speaker identification systems are also suggested.

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“…The positive effect of Quran recitation has already been reported in terms of the signi cant reduction of stress (anxiety) and pain in addition to palliative effects and also signi cant improvement on intra-uterine insemination, concentration, improved quality of dialysis and the vital signs of premature neonates [18][19][20][21][22][23]. A literature review has also revealed that there is a signi cant relationship between Quran Recitation and health and well-being [24].…”

Section: Introductionmentioning

confidence: 99%

Effects of Quran Recitation on The Reduction of Anxiety Before Elective Surgery: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Gavgani¹,

Ghojazadeh²,

Khodapanah³

et al. 2020

Preprint

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Background: Anxiety is a common reaction among patients undergoing surgery. Religious believes are regarded as psychological methods that are used for the management of anxiety. The aim of this study is assessing the effectiveness of Quran recitation on reducing the anxiety before the elective surgery.Methods: A systematic review of the citations in the Medline, EMBASE, Cochrane Library, PsycInfo, Arab World Research Source and other relevant databases was performed to collect the data. Randomized clinical trials about the effect of Quran recitation on the reduction of anxiety before elective surgery were included without any Language and date restriction. Interventions with self-reading/self-recitation were excluded. The Cochran’s Q statistic and the (I2) with 50 percent threshold was used for calculation of the heterogeneity and the inconsistency index. The funnel plot has been used to evaluate the possibility of the publication bias.Results: We identified 2381 studies from the systematic search. Of these, twelve were included in the qualitative synthesis and nine studies included in the quantitative synthesis. Our meta-analysis showed a significant reduction in the anxiety level with Quran recitation. The heterogeneity of the included studies was statistically significant (Q=23.05, I2=65.29, P=0.003). The pooled effect size of the anxiety was d=−8.893; 95% CI=[−10.763 to −7.022] (P < 0.001), and there was no publication bias (t=0.907, P=0.39) in the studies.Conclusion: Quran recitation can be considered as a non-invasive and peaceful intervention to reduce anxiety before elective surgery.

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Phoneme-Based Recognizer to Assist Reading the Holy Quran

Cited by 11 publications

References 3 publications

Discriminative Training for Phonetic Recognition of the Holy Quran

Discriminative Training for Phonetic Recognition of the Holy Quran

Helpful Statistics in Recognizing Basic Arabic Phonemes

Effects of Quran Recitation on The Reduction of Anxiety Before Elective Surgery: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

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