Paper Citation Record · LEDGER

Quantifying Bias in Automatic Speech Recognition

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2103.15122.

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

pith.paper-citation-record.v1
2103.15122 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:04:34.004980Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

53
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 76b42a7c-4816-47a6-9a3b-3690681b3cd7 · inbound

Addressing Pitfalls in Auditing Practices of Automatic Speech Recognition Technologies: A Case Study of People with Aphasia cites this paper.

Addressing Pitfalls in Auditing Practices of Automatic Speech Recognition Technologies: A Case Study of People with Aphasia Quantifying Bias in Automatic Speech Recognition

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T05:04:34.004980Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d215aed5-298e-4216-af3d-48bc84b634ca · inbound

FairASR: Fair Audio Contrastive Learning for Automatic Speech Recognition cites this paper.

FairASR: Fair Audio Contrastive Learning for Automatic Speech Recognition Quantifying Bias in Automatic Speech Recognition

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T04:24:25.050118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1984238a-c4f5-46da-ae58-8927814ea1bb · inbound

Automatic Speech Recognition Biases in Newcastle English: an Error Analysis cites this paper.

Automatic Speech Recognition Biases in Newcastle English: an Error Analysis Quantifying Bias in Automatic Speech Recognition

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T23:42:31.694278Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a03ab24d-d0d1-4280-a41f-d9ac642bd920 · inbound

How to Evaluate Automatic Speech Recognition: Comparing Different Performance and Bias Measures cites this paper.

How to Evaluate Automatic Speech Recognition: Comparing Different Performance and Bias Measures Quantifying Bias in Automatic Speech Recognition

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T19:23:34.623796Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88fb0a85-c879-444a-8279-a6c51f8a8dde · inbound

Speak Your Mind: The Speech Continuation Task as a Probe of Voice-Based Model Bias cites this paper.

Speak Your Mind: The Speech Continuation Task as a Probe of Voice-Based Model Bias Quantifying Bias in Automatic Speech Recognition

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-21T22:40:43.522919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4e4e15f0-d145-4f0b-afea-d084a477fd1e · inbound

Voice, Bias, and Coreference: An Interpretability Study of Gender in Speech Translation cites this paper.

Voice, Bias, and Coreference: An Interpretability Study of Gender in Speech Translation Quantifying Bias in Automatic Speech Recognition

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-17T04:51:31.859484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 51a66e0e-b52b-4a4d-b46a-e874da00ab54 · inbound

ASKD-Whisper: Adaptive Self-knowledge Distillation for Efficient and Low-Latency Automatic Speech Recognition cites this paper.

ASKD-Whisper: Adaptive Self-knowledge Distillation for Efficient and Low-Latency Automatic Speech Recognition Quantifying Bias in Automatic Speech Recognition

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T12:00:57.572649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c513563-6e56-46c7-bf67-f04a521e09bf · inbound

Demographic and Linguistic Bias Evaluation in Omnimodal Language Models cites this paper.

Demographic and Linguistic Bias Evaluation in Omnimodal Language Models Quantifying Bias in Automatic Speech Recognition

Reference 9

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T09:21:01.413941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 44772d09-b6e1-4920-8600-8cbd1df33d48 · inbound

"This Wasn't Made for Me": Recentering User Experience and Emotional Impact in the Evaluation of ASR Bias cites this paper.

"This Wasn't Made for Me": Recentering User Experience and Emotional Impact in the Evaluation of ASR Bias Quantifying Bias in Automatic Speech Recognition

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-09T23:39:43.730289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2ced29c9-9a67-4b75-9f23-e847574e23ff · inbound

Few-Shot Synthetic Accented Speech for ASR Fine-Tuning: What Helps and When? cites this paper.

Few-Shot Synthetic Accented Speech for ASR Fine-Tuning: What Helps and When? Quantifying Bias in Automatic Speech Recognition

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:46:28.547617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4f1082a2-ce1d-4130-8307-94c755f146cd · inbound

Toward Fair Speech Technologies: A Comprehensive Survey of Bias and Fairness in Speech AI cites this paper.

Toward Fair Speech Technologies: A Comprehensive Survey of Bias and Fairness in Speech AI Quantifying Bias in Automatic Speech Recognition

Reference 116

Resolution: verified exact; arxiv_id, observed 2026-05-09T05:50:28.362506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8d6a716f-9e16-47a3-a803-1ecfd0bf783d · inbound

Evaluating Bias in Phoneme-Based Automatic Speech Recognition Systems: An Analysis of IPA Transcription Models cites this paper.

Evaluating Bias in Phoneme-Based Automatic Speech Recognition Systems: An Analysis of IPA Transcription Models Quantifying Bias in Automatic Speech Recognition

Reference 72

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T10:07:55.896480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 75e4db39-74b6-4bda-974c-acce80f07e3f · inbound

Vaani Benchmark V1.0: An Inclusive Multimodal Benchmark Dataset for Hindi cites this paper.

Vaani Benchmark V1.0: An Inclusive Multimodal Benchmark Dataset for Hindi Quantifying Bias in Automatic Speech Recognition

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-07-04T07:39:39.244731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.