Paper Citation Record · LEDGER

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning

As of 21 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 1 inbound Pith citation observation for arXiv:2509.00094.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2509.00094 v1

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

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measured 56 of 56 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T02:16:09.216191Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-11T13:11:03.665834Z

Reference resolution

55 of 55 outbound references displayed

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External citation measurements

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Outbound references

Observation 8d3a7432-0dc0-40fb-92f3-9f02160a38ae · outbound

This paper cites Automatic Pronunciation Assessment -- A Review.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning Automatic Pronunciation Assessment -- A Review

Reference 1

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Observation 20693085-bea7-44ef-ae48-f83e979d73f8 · outbound

This paper cites Enhancing usability of capl system for quran recitation learning.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning Enhancing usability of capl system for quran recitation learning

Reference 2

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Observation a7e18a64-fb83-48ca-8d56-2e117507b18c · outbound

This paper cites Qdat: adatasetforreciting the quran,.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning Qdat: adatasetforreciting the quran,

Reference 3

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Observation 2d2d8b39-59d5-47ef-8587-036398d4e6c5 · outbound

This paper cites Automatic detection of some tajweed rules,.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning Automatic detection of some tajweed rules,

Reference 4

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Observation 2310db9b-f917-4bdf-a434-5ef947d166f8 · outbound

This paper cites Evaluation of the pronunciation of tajweed rules based on dnn as a step towards interactive recitation learning,.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning Evaluation of the pronunciation of tajweed rules based on dnn as a step towards interactive recitation learning,

Reference 5

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Observation f5ba9b09-c6d5-4dab-abc3-f0b9ca49c3b7 · outbound

This paper cites The tarteel dataset: crowd-sourced and labeled quranic recitation,.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning The tarteel dataset: crowd-sourced and labeled quranic recitation,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:22:21.258238Z

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Observation d56b750a-0ba9-4152-a490-3bdb6869bc6c · outbound

This paper cites Towards a Unified Benchmark for Arabic Pronunciation Assessment: Quranic Recitation as Case Study.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning Towards a Unified Benchmark for Arabic Pronunciation Assessment: Quranic Recitation as Case Study

Reference 7

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Observation 3b4c3beb-4878-472e-802f-eb7c48492e23 · outbound

This paper cites A computer aided pronunciation learning system for teaching the holy quran recitation rules,.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning A computer aided pronunciation learning system for teaching the holy quran recitation rules,

Reference 8

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Observation e44ac37c-29b1-45ed-8d44-30af155bc086 · outbound

This paper cites Computeraidedqur’anpronunciationusingdnn,.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning Computeraidedqur’anpronunciationusingdnn,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:22:21.238241Z

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Observation c7750530-a404-4580-94b9-49dd304e1ac6 · outbound

This paper cites Recognition of holy quran recitation rules using phoneme duration,.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning Recognition of holy quran recitation rules using phoneme duration,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:22:21.228270Z

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Observation 032fa7cc-5224-4154-966b-d20f662c534b · outbound

This paper cites Improving automatic forced alignment for phoneme segmentation in quranic recitation,.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning Improving automatic forced alignment for phoneme segmentation in quranic recitation,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:22:21.218628Z

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Observation 3eb7445a-9e22-4ff3-bc2b-cc3a69f2c5d1 · outbound

This paper cites Empirical study on mispronunciation detection for tajweed rules during quran recitation,.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning Empirical study on mispronunciation detection for tajweed rules during quran recitation,

Reference 12

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Observation b92cde1e-24c1-40de-b0a8-801e242cfac3 · outbound

This paper cites Developing speech recog- nition system for quranic verse recitation learning software,.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning Developing speech recog- nition system for quranic verse recitation learning software,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:22:21.198852Z

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Observation aa1d2a60-e942-42c0-83a2-6d425e5e4ee0 · outbound

This paper cites Reducing the dimensionality of data with neural networks,.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning Reducing the dimensionality of data with neural networks,

Reference 14

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This paper cites Neural networks and physical systems with emer- gent collective computational abilities,.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning Neural networks and physical systems with emer- gent collective computational abilities,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:22:21.182457Z

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Observation 0907fce2-8937-4ac5-a5e6-f8af15598837 · outbound

This paper cites Attention is all you need,.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning Attention is all you need,

Reference 16

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Observation af6be107-1afe-438b-b053-a2912aa0ab51 · outbound

This paper cites Bert: Pre- training of deep bidirectional transformers for language understanding,.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning Bert: Pre- training of deep bidirectional transformers for language understanding,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:22:21.162490Z

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Observation 9fd4856e-f8aa-4d72-be37-0229cb13e30a · outbound

This paper cites wav2vec: Unsupervised Pre-training for Speech Recognition.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning wav2vec: Unsupervised Pre-training for Speech Recognition

Reference 18

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This paper cites wav2vec 2.0: A framework for self-supervised learning of speech representations,.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning wav2vec 2.0: A framework for self-supervised learning of speech representations,

Reference 19

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This paper cites Conformer: Convolution-augmented Transformer for Speech Recognition.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning Conformer: Convolution-augmented Transformer for Speech Recognition

Reference 20

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This paper cites W2v-bert: Combining contrastive learning and masked lan- guage modeling for self-supervised speech pre-training,.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning W2v-bert: Combining contrastive learning and masked lan- guage modeling for self-supervised speech pre-training,

Reference 21

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This paper cites Seamless: Multilingual Expressive and Streaming Speech Translation.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning Seamless: Multilingual Expressive and Streaming Speech Translation

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This paper cites Automatic detection of some tajweed rules,.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning Automatic detection of some tajweed rules,

Reference 23

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This paper cites Algorithm 1 Tasmeea Algorithm Require: text_segments = [ s1, s2,.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning Algorithm 1 Tasmeea Algorithm Require: text_segments = [ s1, s2,

Reference 26

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This paper cites Silerovad: pre-trainedenterprise-gradevoiceactivitydetector (vad), number detector and language classifier,.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning Silerovad: pre-trainedenterprise-gradevoiceactivitydetector (vad), number detector and language classifier,

Reference 27

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This paper cites Powerset multi-class cross entropy loss for neural speaker diarization,.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning Powerset multi-class cross entropy loss for neural speaker diarization,

Reference 28

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Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning Audiomentations: Apythonlibraryforaudio data augmentation,

Reference 29

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This paper cites Whisper base arabic quran (automatic speech recognition for quranic recitation),.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning Whisper base arabic quran (automatic speech recognition for quranic recitation),

Reference 30

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Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning Robust speech recognition via large-scale weak supervi- sion,

Reference 31

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This paper cites Connectionist temporal classification: Labelling unsegmented sequence data with recurrent neural networks,.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning Connectionist temporal classification: Labelling unsegmented sequence data with recurrent neural networks,

Reference 32

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Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning Copyright may be transferred without notice, after which this version may no longer be accessible

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Resolution: unresolved; raw_fallback, observed 2026-08-05T15:22:20.915102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0d91358b-93b4-4249-aa1e-84b9203a7903 · outbound

This paper cites an unresolved cited work.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning Unresolved cited work

Reference 51

Resolution: unresolved; raw_fallback, observed 2026-08-05T15:22:20.906389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 364267db-95de-40d6-bc23-40ba3b33fe30 · outbound

This paper cites an unresolved cited work.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning Unresolved cited work

Reference 52

Resolution: unresolved; raw_fallback, observed 2026-08-05T15:22:20.897794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1e2e741c-2357-4c14-b9ef-fdce6373687f · outbound

This paper cites an unresolved cited work.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning Unresolved cited work

Reference 53

Resolution: unresolved; raw_fallback, observed 2026-08-05T15:22:20.888621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 00b66b39-76d9-4f31-b4da-390023c8b433 · outbound

This paper cites an unresolved cited work.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning Unresolved cited work

Reference 54

Resolution: unresolved; raw_fallback, observed 2026-08-05T15:22:20.878917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2761ae5d-d229-42be-9a7d-97fd6f0e471a · outbound

This paper cites an unresolved cited work.

Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning Unresolved cited work

Reference 55

Resolution: unresolved; raw_fallback, observed 2026-08-05T15:22:20.869715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

Observation 2a7c3302-cf31-42c2-a816-b8106e09c0b5 · inbound

Tadabur: A Large-Scale Quran Audio Dataset cites this paper.

Tadabur: A Large-Scale Quran Audio Dataset Automatic Pronunciation Error Detection and Correction of the Holy Quran's Learners Using Deep Learning

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-11T13:11:03.672675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.