Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T23:55:51.156388Z
Paper Citation Record · LEDGER
Enhancing Whisper's Accuracy and Speed for Indian Languages through Prompt-Tuning and Tokenization
As of 16 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2412.19785.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
21 of 21 outbound references displayed
- verified exact1
- verified fuzzy14
- unresolved6
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation e5dd6d60-97be-4fff-9d60-fdb23beb344f · outbound
This paper cites The dawn of the human-machine era: A forecast of new and emerging language technologies.
Enhancing Whisper's Accuracy and Speed for Indian Languages through Prompt-Tuning and Tokenization The dawn of the human-machine era: A forecast of new and emerging language technologies
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T23:55:51.412725Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation c9023926-dbbe-48e9-b0c6-49e1f2a597c6 · outbound
This paper cites Chandramouli and R.
Enhancing Whisper's Accuracy and Speed for Indian Languages through Prompt-Tuning and Tokenization Chandramouli and R
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T23:55:51.400672Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 90f13ce4-3f11-4c77-8b3c-4bc6b3f1cbf0 · outbound
This paper cites An overview of indian spoken language recognition from machine learning perspective,.
Enhancing Whisper's Accuracy and Speed for Indian Languages through Prompt-Tuning and Tokenization An overview of indian spoken language recognition from machine learning perspective,
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T23:55:51.389305Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 7dd02293-d87e-42aa-b091-b7743f5ec5b8 · outbound
This paper cites Robust speech recognition via large-scale weak supervision,.
Enhancing Whisper's Accuracy and Speed for Indian Languages through Prompt-Tuning and Tokenization Robust speech recognition via large-scale weak supervision,
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T23:55:51.088861Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 45112613-4488-4ff4-b3bc-6e9e5a06605a · outbound
This paper cites Scaling speech technology to 1,000+ languages,.
Enhancing Whisper's Accuracy and Speed for Indian Languages through Prompt-Tuning and Tokenization Scaling speech technology to 1,000+ languages,
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T23:55:51.370047Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 2ef100d4-9d11-4d04-b108-837dd40d5583 · outbound
This paper cites Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages.
Enhancing Whisper's Accuracy and Speed for Indian Languages through Prompt-Tuning and Tokenization Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T23:55:51.097120Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b3ed605f-15f2-4567-85ea-a1a1b8e639ee · outbound
This paper cites Enhancing multilin- gual speech recognition through language prompt tuning and frame- level language adapter,.
Enhancing Whisper's Accuracy and Speed for Indian Languages through Prompt-Tuning and Tokenization Enhancing multilin- gual speech recognition through language prompt tuning and frame- level language adapter,
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T23:55:51.359308Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 51076f8e-8739-4529-9f46-5696ab635ba8 · outbound
This paper cites Improving Whisper's Recognition Performance for Under-Represented Language Kazakh Leveraging Unpaired Speech and Text.
Enhancing Whisper's Accuracy and Speed for Indian Languages through Prompt-Tuning and Tokenization Improving Whisper's Recognition Performance for Under-Represented Language Kazakh Leveraging Unpaired Speech and Text
Reference 8
- Resolution
- verified exact
- local_arxiv, observed 2026-08-10T23:55:51.224838Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 36bff5ea-56fd-4e44-af57-4c324c5fb25d · outbound
This paper cites Vistaar: Diverse Benchmarks and Training Sets for Indian Language ASR,.
Enhancing Whisper's Accuracy and Speed for Indian Languages through Prompt-Tuning and Tokenization Vistaar: Diverse Benchmarks and Training Sets for Indian Language ASR,
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T23:55:51.348233Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation de7b300f-3156-43e1-8541-d63e53c53797 · outbound
This paper cites Towards building asr systems for the next billion users,.
Enhancing Whisper's Accuracy and Speed for Indian Languages through Prompt-Tuning and Tokenization Towards building asr systems for the next billion users,
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T23:55:51.337188Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation db58be12-ab7b-479a-ae3d-9220ae65167e · outbound
This paper cites CLSRIL-23: Cross Lingual Speech Representations for Indic Languages.
Enhancing Whisper's Accuracy and Speed for Indian Languages through Prompt-Tuning and Tokenization CLSRIL-23: Cross Lingual Speech Representations for Indic Languages
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T23:55:51.116609Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation afbb9ee6-a563-4dee-9016-983466192e83 · outbound
This paper cites A survey of multilingual models for automatic speech recognition,.
Enhancing Whisper's Accuracy and Speed for Indian Languages through Prompt-Tuning and Tokenization A survey of multilingual models for automatic speech recognition,
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T23:55:51.325646Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation d2b30f47-0f74-4707-8317-1f7d478a1d6f · outbound
This paper cites Large Language Models: A Survey.
Enhancing Whisper's Accuracy and Speed for Indian Languages through Prompt-Tuning and Tokenization Large Language Models: A Survey
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T23:55:51.124453Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 41c9eb04-8927-4bb0-b0bd-d1977d396e2b · outbound
This paper cites Extending whisper with prompt tuning to target-speaker asr,.
Enhancing Whisper's Accuracy and Speed for Indian Languages through Prompt-Tuning and Tokenization Extending whisper with prompt tuning to target-speaker asr,
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T23:55:51.313185Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 91c17447-57ff-496a-9458-e328986db5c2 · outbound
This paper cites The Tag- Team Approach: Leveraging CLS and Language Tagging for Enhancing Multilingual ASR,.
Enhancing Whisper's Accuracy and Speed for Indian Languages through Prompt-Tuning and Tokenization The Tag- Team Approach: Leveraging CLS and Language Tagging for Enhancing Multilingual ASR,
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T23:55:51.301811Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation bd8e0035-2d01-4b2f-a9d7-1ce0a0d3af4d · outbound
This paper cites ASR for Low Resource and Multilin- gual Noisy Code-Mixed Speech,.
Enhancing Whisper's Accuracy and Speed for Indian Languages through Prompt-Tuning and Tokenization ASR for Low Resource and Multilin- gual Noisy Code-Mixed Speech,
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T23:55:51.289856Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 41570dea-6097-4934-8ec1-307076f2ca93 · outbound
This paper cites Improving low-resource languages in pre-trained multilingual language models,.
Enhancing Whisper's Accuracy and Speed for Indian Languages through Prompt-Tuning and Tokenization Improving low-resource languages in pre-trained multilingual language models,
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T23:55:51.278197Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation b2c20fae-be94-4187-bd9f-aef03291396e · outbound
This paper cites Indicsuperb: A speech processing universal performance benchmark for indian languages,.
Enhancing Whisper's Accuracy and Speed for Indian Languages through Prompt-Tuning and Tokenization Indicsuperb: A speech processing universal performance benchmark for indian languages,
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T23:55:51.266473Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 22f69188-7c22-4d6b-94c1-2d89afed0fc3 · outbound
This paper cites Language models are unsupervised multitask learners,.
Enhancing Whisper's Accuracy and Speed for Indian Languages through Prompt-Tuning and Tokenization Language models are unsupervised multitask learners,
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T23:55:51.148277Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b1cd9dbe-8581-4070-aad6-a0915f7abc04 · outbound
This paper cites WhisperX: Time-Accurate Speech Transcription of Long-Form Audio.
Enhancing Whisper's Accuracy and Speed for Indian Languages through Prompt-Tuning and Tokenization WhisperX: Time-Accurate Speech Transcription of Long-Form Audio
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T23:55:51.152222Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 56843f6e-291c-43a1-8c52-adbf5f444ca3 · outbound
This paper cites faster-whisper: Faster whisper transcription and translation model,.
Enhancing Whisper's Accuracy and Speed for Indian Languages through Prompt-Tuning and Tokenization faster-whisper: Faster whisper transcription and translation model,
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T23:55:51.247519Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Pith citing papers
No inbound Pith citation observations are available.