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Paper Citation Record · LEDGER

ASR-FAIRBENCH: Measuring and Benchmarking Equity Across Speech Recognition Systems

As of 16 August 2026, this Paper Citation Record lists 11 of 11 outbound references and 2 inbound Pith citation observations for arXiv:2505.11572.

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

pith.paper-citation-record.v1
2505.11572 v1

Coverage vector

measured 11 of 11 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:00:59.321654Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:00:59.263827Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T10:24:22.076360Z

Reference resolution

11 of 11 outbound references displayed

  • verified exact0
  • verified fuzzy7
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 99cc254e-3ecf-49a6-bf89-d1972131c542 · outbound

This paper cites However, despite impressive strides in overall accuracy, these systems of- ten exhibit significant performance disparities across diverse demographic groups.

ASR-FAIRBENCH: Measuring and Benchmarking Equity Across Speech Recognition Systems However, despite impressive strides in overall accuracy, these systems of- ten exhibit significant performance disparities across diverse demographic groups

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:00:59.533207Z

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.

source=pdf_text observed=2026-08-15T21:00:59.256145Z digest=sha256:747d15957b421a85302f48f3797bbf7a00dfb7801d3a92d0ab2be011a19bbe05

Observation 9837e751-2b81-4558-acf8-c2f82c2a2d15 · outbound

This paper cites ASR-FAIRBENCH: Measuring and Benchmarking Equity Across Speech Recognition Systems.

ASR-FAIRBENCH: Measuring and Benchmarking Equity Across Speech Recognition Systems ASR-FAIRBENCH: Measuring and Benchmarking Equity Across Speech Recognition Systems

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-15T21:00:59.263827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:00:59.263827Z digest=sha256:df1da7e90bc725939156860179eccc714ee9f637eebe757b8f2cb6fc9b54eb53

Observation 8e9a807f-717c-4a81-8dcb-3f7da1aa56ff · outbound

This paper cites Built with React.js, leveraging an NVIDIA T4 GPU for inference, it of- fers an interactive platform for model submissions, performance analysis, and real-time leaderboard tracking.

ASR-FAIRBENCH: Measuring and Benchmarking Equity Across Speech Recognition Systems Built with React.js, leveraging an NVIDIA T4 GPU for inference, it of- fers an interactive platform for model submissions, performance analysis, and real-time leaderboard tracking

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:00:59.517607Z

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.

source=pdf_text observed=2026-08-15T21:00:59.270205Z digest=sha256:1454adcba1724690ed5809b9e6ef9212fbed9ad6ca0dad0d6059af9eb8f599a5

Observation 2e3559ac-5ebb-4d99-9c85-90dc1ad90d50 · outbound

This paper cites Despite higher 1https://huggingface.co/spaces/satyamr196/ASR-FairBench 2https://github.com/SatyamR196/ASR-FairBench (a) ASR-F AIRBENCHleaderboard (b) Summarized results view.

ASR-FAIRBENCH: Measuring and Benchmarking Equity Across Speech Recognition Systems Despite higher 1https://huggingface.co/spaces/satyamr196/ASR-FairBench 2https://github.com/SatyamR196/ASR-FairBench (a) ASR-F AIRBENCHleaderboard (b) Summarized results view

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:00:59.503021Z

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.

source=pdf_text observed=2026-08-15T21:00:59.277548Z digest=sha256:351b292b373048c064f668c811f2de086657c6627f3663e4897402a2fdf0d6c3

Observation cfc7689a-6888-422b-bffb-5e488ddcbca1 · outbound

This paper cites Effects of talker dialect, gender & race on accuracy of bing speech and youtube automatic captions.

ASR-FAIRBENCH: Measuring and Benchmarking Equity Across Speech Recognition Systems Effects of talker dialect, gender & race on accuracy of bing speech and youtube automatic captions

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:00:59.484218Z

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.

source=pdf_text observed=2026-08-15T21:00:59.282491Z digest=sha256:776f387e1313fd9436e6f30f1d4d9a0df603d79f3c63b0b66dc698dfcc4ed017

Observation d267d497-0d84-47ae-92fb-bf46a61e906e · outbound

This paper cites Quantifying Bias in Automatic Speech Recognition.

ASR-FAIRBENCH: Measuring and Benchmarking Equity Across Speech Recognition Systems Quantifying Bias in Automatic Speech Recognition

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-15T21:00:59.289473Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:00:59.289473Z digest=sha256:31ec38c5e30b695abd70fd9cceae709b31821410aec57909f3bfa2a4d038fb1c

Observation b4480df1-6d53-4f3c-a957-e65a67ebdebc · outbound

This paper cites A deep dive into the disparity of word error rates across thousands of nptel mooc videos,.

ASR-FAIRBENCH: Measuring and Benchmarking Equity Across Speech Recognition Systems A deep dive into the disparity of word error rates across thousands of nptel mooc videos,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:00:59.467725Z

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.

source=pdf_text observed=2026-08-15T21:00:59.296205Z digest=sha256:e6f43ed7e5c2c5dd776f8d8a3be8c01aa8d6eafc2d33276e0acf76fa0a46a902

Observation 3d34d9b3-e01e-4ea0-af8a-f43f2635d890 · outbound

This paper cites Open Universal Arabic ASR Leaderboard.

ASR-FAIRBENCH: Measuring and Benchmarking Equity Across Speech Recognition Systems Open Universal Arabic ASR Leaderboard

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-15T21:00:59.303453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:00:59.303453Z digest=sha256:61c6d1168da6058d3550634abb46b55f1a409bd4fbd57b6f383542db6514b57f

Observation d4101789-f09a-4560-aae7-07bf18482e2e · outbound

This paper cites Open automatic speech recognition leaderboard,.

ASR-FAIRBENCH: Measuring and Benchmarking Equity Across Speech Recognition Systems Open automatic speech recognition leaderboard,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:00:59.452396Z

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.

source=pdf_text observed=2026-08-15T21:00:59.310087Z digest=sha256:ce363f27a72b7c4de1356bc5d993a727762e78dff88bd4ce07163f1f9aa2c685

Observation 60c8a55f-f009-4c89-84d5-46364cc91673 · outbound

This paper cites Racial disparities in automated speech recognition,.

ASR-FAIRBENCH: Measuring and Benchmarking Equity Across Speech Recognition Systems Racial disparities in automated speech recognition,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:00:59.435357Z

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.

source=pdf_text observed=2026-08-15T21:00:59.316000Z digest=sha256:7d6b66afc2494be5262496d4d32c4a006db3339e7b4384c900b0268687fe1bdc

Observation 2067908b-8826-465d-a960-0557251d5cf5 · outbound

This paper cites Towards measuring fairness in speech recognition: Fair-Speech dataset.

ASR-FAIRBENCH: Measuring and Benchmarking Equity Across Speech Recognition Systems Towards measuring fairness in speech recognition: Fair-Speech dataset

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-15T21:00:59.321654Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:00:59.321654Z digest=sha256:f02951b6a4b9d5482f0ce42a8e8ee9c39e350de81762b04bfd101a4c524f16c2

Pith citing papers

Observation 9837e751-2b81-4558-acf8-c2f82c2a2d15 · inbound

ASR-FAIRBENCH: Measuring and Benchmarking Equity Across Speech Recognition Systems cites this paper.

ASR-FAIRBENCH: Measuring and Benchmarking Equity Across Speech Recognition Systems ASR-FAIRBENCH: Measuring and Benchmarking Equity Across Speech Recognition Systems

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-15T21:00:59.263827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:00:59.263827Z digest=sha256:df1da7e90bc725939156860179eccc714ee9f637eebe757b8f2cb6fc9b54eb53

Observation c4f62e71-3d25-4eca-92f3-d2fdff392312 · inbound

VoxSafeBench: Not Just What Is Said, but Who, How, and Where cites this paper.

VoxSafeBench: Not Just What Is Said, but Who, How, and Where ASR-FAIRBENCH: Measuring and Benchmarking Equity Across Speech Recognition Systems

Reference 69

Resolution
verified exact
arxiv_id, observed 2026-05-10T10:24:22.079219Z

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.

source=pdf_text observed=2026-05-10T10:19:28.041282Z digest=sha256:295abe97c1d7abba6007c00458b6f6acf1ad9e26012d1264fb820b75a49763b9