Levent Sagun: speech tech × responsible AI; queer inclusion and participatory speech dataset curation
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—
Not yet scored: no aggregated publication-count or venue-quality data is available in this snapshot. This axis would measure total research output — number of publications, venues, and authorship roles — over time.
Impact—
Not yet scored: citation counts and downstream uptake are absent from this snapshot. This axis would measure influence — citations, adoption of the datasets or frameworks proposed, and uptake in policy or community practice.
Focus0/100
Scores 0 on the 0–100 focus scale. The underlying field distribution splits evenly at 50/50 between two closely related labels — speech technology / responsible AI and its fairness, accountability, and transparency variant — so the metric registers no dominant field. In practice both catalogued 2026 papers address the same queer-inclusion topic, but with only two labelled entries the provided data cannot support a higher focus score.
Collaboration28/100
Scores 28 on the collaboration scale, computed from 3 distinct co-authors in the available data. Recurring collaborators are Brooklyn Sheppard, Anaelia Ovalle, and Adina Williams. Both 2026 papers place Sagun in the last-author position without corresponding-author designation, consistent with a senior advisory role. The small network reflects a compact, stable team rather than a broad collaboration graph, though the observed window covers only the two catalogued papers.
Activity—
Not yet scored: the snapshot lacks multi-year publication frequency and calendar data. This axis would measure research tempo — papers per year, gaps between releases, and sustained presence in the literature — none of which can be computed from two dated entries.
Reproducibility20/100
Scores 20, the mean across the 2 papers with reproducibility assessments, both rated low readiness. The dataset audit is descriptive with thin statistics, and the participatory curation framework is a conceptual position paper with no pilot or empirical validation. Both outputs are arXiv preprints. Reproducibility would likely rise with released annotation protocols, dataset documentation, and pilot studies validating the proposed framework.
Research summary
Levent Sagun (ORCID 0000-0001-5403-4124; name-resolved from public bibliographic data) works at the intersection of speech technology and responsible AI, with a current focus on queer inclusion in speech datasets. The Evolve catalog holds two 2026 arXiv papers, both with Sagun in the last-author position and neither as corresponding author. The first audits eight speech datasets, reporting queer speakers at only 0–1.4% and proposing a four-way taxonomy of practical tensions around gender annotation and dataset construction; Evolve judges it descriptive but solid and timely, with thin statistics. The second is a position paper introducing a four-phase participatory framework for queer speech dataset curation, grounded in a queer case study; it is assessed as timely and well-motivated but unvalidated, with no pilot or supporting evidence. Both papers carry low reproducibility-readiness ratings, consistent with the radar reproducibility score of 20 (mean across 2 assessed papers). Computable radar dimensions show collaboration at 28 from 3 distinct co-authors — recurring collaborators Brooklyn Sheppard, Anaelia Ovalle, and Adina Williams — and focus at 0, reflecting an even 50/50 split across two closely related field labels. Output, impact, and activity lack underlying data and are reported as missing.
Collaboration pattern
The observed collaboration footprint is compact: 3 distinct co-authors, with Brooklyn Sheppard, Anaelia Ovalle, and Adina Williams recurring across the catalogued work. On both 2026 papers Sagun appears as last author without corresponding-author designation, a senior-advisory authorship pattern. The recurring trio and consistent positioning suggest a small, stable team working jointly on queer inclusion in speech datasets rather than a wide network of ad-hoc collaborations.
Research keywords
Highlights
Audit of eight speech datasets finds only 0–1.4% queer speakers
Four-phase participatory framework for queer speech data curation
A defined agenda: queer inclusion in speech technology
Both catalogued 2026 papers converge on the same question — how speech datasets represent and include queer speakers — pairing empirical auditing with participatory design and placing responsible AI concerns at the center of Sagun's current output.
Timeline
- 2026Audits eight speech datasets on arXiv, finding queer speakers at just 0–1.4% and proposing a four-way taxonomy of practical tensions in gender annotation and dataset construction (last author).
- 2026Publishes a position paper proposing a four-phase participatory framework for queer speech dataset curation, grounded in a queer case study (last author).
- 2026Both catalogued papers appear within the same year, forming a concentrated line of work on queer inclusion and participatory curation in speech technology.
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.
- Radar scores derive from a thin bibliometric snapshot (2 catalogued papers, 3 distinct co-authors) and should be read as provisional.
- Identity is name-resolved from public bibliographic data anchored to ORCID 0000-0001-5403-4124; institution and country are not provided.
- Output, impact, and activity dimensions lack underlying data and are reported as missing rather than estimated.
- Coverage is limited to the two 2026 arXiv papers reviewed by Evolve; no citation counts, venue records, or funding information are available.