Paper Citation Record · LEDGER

Assessing the Feasibility of Lightweight Whisper Models for Low-Resource Urdu Transcription

As of 20 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2508.09865.

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

pith.paper-citation-record.v1
2508.09865 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T20:48:03.828569Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

19 of 19 outbound references displayed

verified exact0
verified fuzzy16
unresolved3
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4ded10b6-0d50-4b76-a788-6892e44cd788 · outbound

This paper cites Speech recognition with deep recur- rent neural networks,.

Assessing the Feasibility of Lightweight Whisper Models for Low-Resource Urdu Transcription Speech recognition with deep recur- rent neural networks,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:48:03.990780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 32330010-d56f-445d-891c-cc553ea5b6fe · outbound

This paper cites A survey on advancements in voice control systems enhancing human-computer interaction through speech recog- nition and ai,.

Assessing the Feasibility of Lightweight Whisper Models for Low-Resource Urdu Transcription A survey on advancements in voice control systems enhancing human-computer interaction through speech recog- nition and ai,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:48:03.983787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fa9d25a4-86ca-4625-9f85-5a0c07a215ee · outbound

This paper cites Advancements in speech recognition: A systematic review of deep learning transformer models, trends, innovations, and future directions,.

Assessing the Feasibility of Lightweight Whisper Models for Low-Resource Urdu Transcription Advancements in speech recognition: A systematic review of deep learning transformer models, trends, innovations, and future directions,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:48:03.976730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation be7140c4-98a1-4e6f-aed2-2d8ea9071952 · outbound

This paper cites Self-supervised speech representation learning: A review,.

Assessing the Feasibility of Lightweight Whisper Models for Low-Resource Urdu Transcription Self-supervised speech representation learning: A review,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:48:03.968361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a342ca78-a392-4390-839f-55704f72fd93 · outbound

This paper cites Ai-powered innovations for doc- umenting and revitalizing african languages,.

Assessing the Feasibility of Lightweight Whisper Models for Low-Resource Urdu Transcription Ai-powered innovations for doc- umenting and revitalizing african languages,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:48:03.961464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d7b32ee8-c9e7-4ce4-8b66-d9e6dea35e83 · outbound

This paper cites Robust speech recognition via large-scale weak su- pervision,.

Assessing the Feasibility of Lightweight Whisper Models for Low-Resource Urdu Transcription Robust speech recognition via large-scale weak su- pervision,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:48:03.954234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 18ce3ed9-671e-4893-9d8a-192cb6ddb3e8 · outbound

This paper cites Code-switched urdu asr for noisy telephonic environment using data centric approach with hy- brid hmm and cnn-tdnn,.

Assessing the Feasibility of Lightweight Whisper Models for Low-Resource Urdu Transcription Code-switched urdu asr for noisy telephonic environment using data centric approach with hy- brid hmm and cnn-tdnn,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:48:03.946903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 08c6bddf-4b2d-4dac-985b-330eb288f883 · outbound

This paper cites A survey of speech recognition on south indian lan- guages,.

Assessing the Feasibility of Lightweight Whisper Models for Low-Resource Urdu Transcription A survey of speech recognition on south indian lan- guages,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:48:03.938712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation affe56d9-016e-4d70-ac01-cb8b035dd876 · outbound

This paper cites Fine-tuning whisper tiny for Swahili ASR: Challenges and recommendations for low-resource speech recognition,.

Assessing the Feasibility of Lightweight Whisper Models for Low-Resource Urdu Transcription Fine-tuning whisper tiny for Swahili ASR: Challenges and recommendations for low-resource speech recognition,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:48:03.930718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 099bfd07-03ba-41ed-8748-32e5bfeb3c80 · outbound

This paper cites Improving large vo- cabulary urdu speech recognition system using deep neural networks,.

Assessing the Feasibility of Lightweight Whisper Models for Low-Resource Urdu Transcription Improving large vo- cabulary urdu speech recognition system using deep neural networks,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:48:03.921564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7841776f-55b6-4cba-bb26-e3d896750317 · outbound

This paper cites Audd: Audio urdu digits dataset for automatic audio urdu digit recognition,.

Assessing the Feasibility of Lightweight Whisper Models for Low-Resource Urdu Transcription Audd: Audio urdu digits dataset for automatic audio urdu digit recognition,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:48:03.913061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 895f1b79-a096-4b11-8568-2980f5d33d61 · outbound

This paper cites From Statistical Methods to Pre-Trained Models; A Survey on Automatic Speech Recognition for Resource Scarce Urdu Language.

Assessing the Feasibility of Lightweight Whisper Models for Low-Resource Urdu Transcription From Statistical Methods to Pre-Trained Models; A Survey on Automatic Speech Recognition for Resource Scarce Urdu Language

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-05T20:48:03.807953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3b37052a-b920-4dde-a8ce-9c11759fbd85 · outbound

This paper cites Hey asr system! why aren’t you more inclusive? automatic speech recognition systems’ bias and proposed bias mitigation techniques. a literature review,.

Assessing the Feasibility of Lightweight Whisper Models for Low-Resource Urdu Transcription Hey asr system! why aren’t you more inclusive? automatic speech recognition systems’ bias and proposed bias mitigation techniques. a literature review,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:48:03.903955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation cbe2bd28-0242-4a4c-8a58-4b6a8b77bcba · outbound

This paper cites an unresolved cited work.

Assessing the Feasibility of Lightweight Whisper Models for Low-Resource Urdu Transcription Unresolved cited work

Reference 14

Resolution: unresolved; raw_fallback, observed 2026-08-05T20:48:03.896008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d1931481-8216-4690-abf3-7224f424d851 · outbound

This paper cites Evaluating ope- nai’s whisper asr: Performance analysis across di- verse accents and speaker traits,.

Assessing the Feasibility of Lightweight Whisper Models for Low-Resource Urdu Transcription Evaluating ope- nai’s whisper asr: Performance analysis across di- verse accents and speaker traits,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:48:03.888175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation cd4fe121-3c6f-4315-9477-eb0ae9352108 · outbound

This paper cites Asr systems under acoustic challenges: A multilingual study,.

Assessing the Feasibility of Lightweight Whisper Models for Low-Resource Urdu Transcription Asr systems under acoustic challenges: A multilingual study,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:48:03.880191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3ece2042-b4a5-40b3-8f86-cb71e8dbd07d · outbound

This paper cites Enhancing multilingual asr for unseen languages via language embedding model- ing,.

Assessing the Feasibility of Lightweight Whisper Models for Low-Resource Urdu Transcription Enhancing multilingual asr for unseen languages via language embedding model- ing,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:48:03.872551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e74e2823-be39-4fd1-b524-1786f414069f · outbound

This paper cites Enabling asr for low-resource languages: A comprehensive dataset creation approach,.

Assessing the Feasibility of Lightweight Whisper Models for Low-Resource Urdu Transcription Enabling asr for low-resource languages: A comprehensive dataset creation approach,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:48:03.863784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 49494215-10c4-414c-87af-0e27f7743fa6 · outbound

This paper cites WER We Stand: Benchmarking Urdu ASR Models.

Assessing the Feasibility of Lightweight Whisper Models for Low-Resource Urdu Transcription WER We Stand: Benchmarking Urdu ASR Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-05T20:48:03.828569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.