Paper Citation Record · LEDGER

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data

As of 14 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 1 inbound Pith citation observation for arXiv:2411.09431.

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

pith.paper-citation-record.v1
2411.09431 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T20:42:40.095369Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-15T00:03:31.986628Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

41 of 41 outbound references displayed

verified exact0
verified fuzzy32
unresolved9
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External citation measurements

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Outbound references

Observation 4f08074b-7fa3-4290-aa0b-1e6f4874d293 · outbound

This paper cites an unresolved cited work.

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data Unresolved cited work

Reference 1

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Observation f672a42d-2b0a-41e1-b89a-317dfbed2020 · outbound

This paper cites Available at SSRN (2016).

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data Available at SSRN (2016)

Reference 2

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Observation 8484836c-7d02-49a9-b0a0-c48bc5308321 · outbound

This paper cites Common Voice: A Massively-Multilingual Speech Corpus.

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data Common Voice: A Massively-Multilingual Speech Corpus

Reference 3

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Observation e9b5af71-7ffd-4e12-bd04-a1ac6197b98e · outbound

This paper cites Unmasking Contextual Stereotypes: Measuring and Mitigating BERT's Gender Bias.

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data Unmasking Contextual Stereotypes: Measuring and Mitigating BERT's Gender Bias

Reference 4

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Observation 701fc843-106a-408d-b8f0-75aead89bf35 · outbound

This paper cites Cognitive Computation 13(4), 1008–1018 (2021).

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data Cognitive Computation 13(4), 1008–1018 (2021)

Reference 5

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Observation 644c212c-7550-4062-8e68-f8a0c4076fe1 · outbound

This paper cites Language (Technology) is Power: A Critical Survey of "Bias" in NLP.

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data Language (Technology) is Power: A Critical Survey of "Bias" in NLP

Reference 6

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Observation 2f164cea-eb2a-4e93-aa94-7ded69bf97a2 · outbound

This paper cites ACM SIGKDD explorations newsletter 1(2), 1–11 (2000).

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data ACM SIGKDD explorations newsletter 1(2), 1–11 (2000)

Reference 7

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Observation a5b8b945-d459-495d-b3a2-b34831e55775 · outbound

This paper cites In: Proceedings of the 23rd Conference of the International Speech Communication Association (2022).

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data In: Proceedings of the 23rd Conference of the International Speech Communication Association (2022)

Reference 8

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Observation 45793009-2137-4392-a575-b2e79750fca8 · outbound

This paper cites Journal of accounting and economics 12(1-3), 15–36 (1990).

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data Journal of accounting and economics 12(1-3), 15–36 (1990)

Reference 9

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Observation 269917f2-62fd-4e0f-843a-f3a457e0e180 · outbound

This paper cites (12 2017), nIPS 2017 Keynote.

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data (12 2017), nIPS 2017 Keynote

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:42:40.682304Z

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Observation 4ae23278-6905-43f4-88af-ebabc809ec03 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 11

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Observation 489e9f88-958d-4922-83aa-3dbf33afb75f · outbound

This paper cites Procedia Computer Science128, 32–37 (2018) 4 https://npo.nl/ Analyzing Predictive Gender Bias in Dutch ASR 15.

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data Procedia Computer Science128, 32–37 (2018) 4 https://npo.nl/ Analyzing Predictive Gender Bias in Dutch ASR 15

Reference 12

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Observation 136fdc52-e5e8-47a0-b6c1-56583534e4c3 · outbound

This paper cites Computer Speech & Language p.

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data Computer Speech & Language p

Reference 13

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Observation 7e4c14c6-c8e3-47e5-84d7-bd9c869520ed · outbound

This paper cites Quantifying Bias in Automatic Speech Recognition.

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data Quantifying Bias in Automatic Speech Recognition

Reference 14

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Observation 022643f2-bd42-4193-8ec1-202ce81eda2a · outbound

This paper cites In: 2023 International Conference on Speech Technology and Human-Computer Dialogue (SpeD).

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data In: 2023 International Conference on Speech Technology and Human-Computer Dialogue (SpeD)

Reference 15

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Observation 79271920-4dd1-40b9-ae86-bb48fccb267f · outbound

This paper cites In: Proceedings of the 1st international workshop on AI for smart TV content production, access and delivery.

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data In: Proceedings of the 1st international workshop on AI for smart TV content production, access and delivery

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:42:40.621848Z

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Observation 3423b6c9-558e-4a3b-89a0-2701a552e085 · outbound

This paper cites In: 3rd Workshop on Gender Bias in Natural Language Processing.

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data In: 3rd Workshop on Gender Bias in Natural Language Processing

Reference 17

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Observation 45ebde54-8f4b-4eba-9d8f-79fa3a0d0af0 · outbound

This paper cites Scaling Laws for Neural Machine Translation.

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data Scaling Laws for Neural Machine Translation

Reference 18

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This paper cites In: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency.

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data In: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency

Reference 19

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Observation d040cec6-aa33-4ef8-a372-28e25a864053 · outbound

This paper cites In: Pro- ceedings of the 54th Annual Meeting of the Association for Computational Lin- guistics (Volume 2: Short Papers).

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data In: Pro- ceedings of the 54th Annual Meeting of the Association for Computational Lin- guistics (Volume 2: Short Papers)

Reference 20

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Observation 9c4ad86e-fadc-4454-96cf-872a0fe910b5 · outbound

This paper cites In: The 2024 ACM Conference on Fair- ness, Accountability, and Transparency.

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data In: The 2024 ACM Conference on Fair- ness, Accountability, and Transparency

Reference 21

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Observation 2fd96ab8-82c4-4185-87c5-c8a6a716ca0c · outbound

This paper cites Information Sciences 177(22), 4893–4905 (2007).

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data Information Sciences 177(22), 4893–4905 (2007)

Reference 22

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Observation 4db69d98-b41b-4aed-816d-52e134313a5a · outbound

This paper cites In: 1st ACL Workshop on Gender Bias for Natural Language Processing (2019).

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data In: 1st ACL Workshop on Gender Bias for Natural Language Processing (2019)

Reference 23

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This paper cites Social psychological and personality science8(4), 355–362 (2017).

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data Social psychological and personality science8(4), 355–362 (2017)

Reference 24

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This paper cites In: ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data In: ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Reference 25

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This paper cites In: ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Reference 26

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Observation 7cd44b8c-e633-4f96-b4a0-6042060546e3 · outbound

This paper cites In: Proceedings of the Twelfth Language Resources and Evaluation Conference.

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data In: Proceedings of the Twelfth Language Resources and Evaluation Conference

Reference 27

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This paper cites In: Interspeech.

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data In: Interspeech

Reference 28

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This paper cites BBC News, Jan (2017).

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data BBC News, Jan (2017)

Reference 29

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This paper cites NPJ digital medicine2(1), 55 (2019).

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data NPJ digital medicine2(1), 55 (2019)

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:42:40.417821Z

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This paper cites Robust Speech Recognition via Large-Scale Weak Supervision.

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data Robust Speech Recognition via Large-Scale Weak Supervision

Reference 31

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This paper cites In: Proceedings of the 2nd Workshop of Arabic Corpus Linguistics WACL-2.

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data In: Proceedings of the 2nd Workshop of Arabic Corpus Linguistics WACL-2

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:42:40.402420Z

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Observation 19c3e429-af76-4c04-893a-d1b61ac12734 · outbound

This paper cites NPR All Things Considered (2015).

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data NPR All Things Considered (2015)

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:42:40.386171Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 35878645-d891-4041-8930-5fe7638235cf · outbound

This paper cites Biometrika 52(3/4), 591–611 (1965).

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data Biometrika 52(3/4), 591–611 (1965)

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:42:40.369880Z

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This paper cites In: Equity and access in algorithms, mechanisms, and optimization, pp.

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data In: Equity and access in algorithms, mechanisms, and optimization, pp

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:42:40.353629Z

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This paper cites In: Proceed- ings of the first ACL workshop on ethics in natural language processing.

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data In: Proceed- ings of the first ACL workshop on ethics in natural language processing

Reference 36

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Observation 76cf22b4-ffa7-4653-9e2e-5a005f901f3a · outbound

This paper cites In: Interspeech.

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data In: Interspeech

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:42:40.318629Z

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Observation 67572aff-1612-4c57-8682-b635a695f9aa · outbound

This paper cites In: Speech and Natural Language: Proceedings of a Workshop Held at Philadelphia, Pennsylvania, February 21-23, 1989 (1989).

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data In: Speech and Natural Language: Proceedings of a Workshop Held at Philadelphia, Pennsylvania, February 21-23, 1989 (1989)

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:42:40.303091Z

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This paper cites Are There Exceptions to Goodhart's Law? On the Moral Justification of Fairness-Aware Machine Learning.

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data Are There Exceptions to Goodhart's Law? On the Moral Justification of Fairness-Aware Machine Learning

Reference 39

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Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data In: Proc

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:42:40.286387Z

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Observation 3c6c13ce-2d41-4a75-bf7e-9eea1c296344 · outbound

This paper cites In: Proceedings of the Annual Conference of the In- ternational Speech Communication Association, INTERSPEECH.

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data In: Proceedings of the Annual Conference of the In- ternational Speech Communication Association, INTERSPEECH

Reference 41

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Pith citing papers

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A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition cites this paper.

A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data

Reference 36

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