Early-career researcher in speech technology and responsible AI, focused on queer inclusion in speech datasets.
2
papers here
2
reviewed by Evolve
0
first-author
0
corresponding
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works · OpenAlex
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h-index · OpenAlex
Bibliometric figures come from OpenAlex (2026-10-08) and cover the author's entire public record, not just the papers listed here. Reproducibility signal comes from Evolve's own reviews.
Research profile
Output—
No output metrics are available yet. This axis would measure total publication volume, venue types (preprint versus peer-reviewed), and authorship positions over time; with only two 2026 arXiv preprints in scope, a productivity score cannot be computed honestly.
Impact—
Impact data is not yet available. This axis would measure citations, downstream reuse of the dataset audit and curation framework, and uptake by the speech and responsible-AI communities; with no citation signals in the input, no estimate is made.
Focus0/100
The focus axis computes to 0, while the raw field distribution splits evenly (0.5/0.5) between two nearly identical labels: speech technology / responsible AI and its fairness, accountability, transparency strand. Topically, both cataloged papers target queer inclusion in speech datasets, suggesting a coherent niche rather than scattered interests. With only two papers feeding the metric, this score reflects a very thin evidence base and should be read cautiously.
Collaboration28/100
The collaboration axis scores 28, based on a small observed network: 3 distinct co-authors across the cataloged work, with Brooklyn Sheppard, Adina Williams, and Levent Sagun appearing as frequent collaborators. Both papers list Ovalle in a middle authorship position without corresponding-author roles. This indicates early, small-team collaboration rather than large consortium work; the network picture rests on two 2026 preprints and may understate actual co-authorship.
Activity—
Activity metrics are missing from the current snapshot. This axis would measure annual publication cadence and sustained research tempo across years; the catalog only covers 2026, so year-over-year activity cannot be scored without guessing.
Reproducibility20/100
Reproducibility scores 20, computed as a mean of 20 across the 2 reproducibility-assessed papers, each rated low readiness. Evolve's review finds the dataset audit descriptive with thin statistics, and the participatory curation framework unvalidated, with no pilot or empirical evidence. At this stage, reproducibility rests on the audit's documented dataset sample rather than validated methods or empirical evidence.
Research summary
Anaelia Ovalle is an early-stage researcher working at the intersection of speech technology and responsible AI, focusing on how queer and LGBTQIA+ communities are represented in speech datasets. The Evolve catalog currently holds two 2026 arXiv papers, both middle-author contributions approaching the problem from complementary directions. One audits eight speech datasets, reporting queer speaker representation of only 0–1.4% and proposing a four-way taxonomy of practical tensions around gender annotation and inclusion. The other is a position paper introducing a four-phase participatory framework for queer speech dataset curation, grounded in co-design, data governance, and community participation. Evolve's review characterizes both as timely and well-motivated but unvalidated: the audit is descriptive with thin statistics, and the framework has no pilot evidence, leaving both with low reproducibility readiness. The bibliometric footprint is narrow — 3 distinct co-authors (Brooklyn Sheppard, Adina Williams, Levent Sagun), a field distribution split evenly between responsible-AI speech work and its fairness, accountability, transparency strand, and low computed scores for collaboration (28) and reproducibility (20). Output, impact, and activity metrics are not yet available. This profile is name-resolved from public bibliographic data; no institutional affiliation is on record.
Collaboration pattern
Ovalle's visible collaboration footprint is compact: 3 distinct co-authors across the catalog, with Brooklyn Sheppard, Adina Williams, and Levent Sagun as recurring collaborators. Both 2026 papers carry middle authorship without corresponding roles, consistent with contributing within a small team rather than leading one. The low collaboration score (28) reflects this small network in the current snapshot; it is derived from only two preprints and may change quickly as the record grows.
Research keywords
Highlights
Audit quantifies queer underrepresentation in 8 speech datasets
Four-phase participatory framework for queer speech data curation
Timeline
- 2026Co-authored the arXiv audit "Queer inclusion in speech datasets", reporting 0–1.4% queer speaker representation across 8 datasets and proposing a four-way tension taxonomy.
- 2026Co-authored the arXiv position paper "Towards participatory speech dataset curation", proposing a four-phase participatory framework for queer speech data curation.
- 2026Both cataloged papers appear in the same year, concentrating the record on queer inclusion in speech technology and responsible AI.
Papers in the Evolve catalog
Frequent co-authors
About this profile
This profile is AI-structured by Evolve.Pub from public bibliographic data (OpenAlex) and Evolve's own paper reviews. It is not written or endorsed by the researcher unless the profile is claimed. Radar dimensions are computed from real bibliometrics with fixed formulas — raw figures are shown alongside; missing dimensions mean insufficient data, never zero. Errors? Claim the profile to correct or hide it.
- Bibliometric dimensions and scores are derived from OpenAlex-based public bibliometric data only; institution and country are not on record.
- Output, impact, and activity axes lack sufficient underlying data and are reported as missing rather than scored.
- Both cataloged papers are 2026 arXiv preprints with low reproducibility readiness; this snapshot includes no peer-reviewed venue or citation data.
- Profile is name-resolved from public bibliographic data (ORCID 0000-0002-0531-7520); identity matching relies on bibliographic linkage.