# Towards participatory speech dataset curation: A queer case study and conceptual framework

arXiv: https://arxiv.org/abs/2609.25496 · HTML: https://mlsanity.com/paper/2609.25496/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 15 of its 33 references that are in the map.
- First posted on arXiv 21 Sep 2026.

## Builds on (most cited first, 15 of 15)

- [Participation is not a Design Fix for Machine Learning](https://mlsanity.com/paper/2007.02423/) (2020)
- [Fairness for Unobserved Characteristics: Insights from Technological Impacts on Queer Communities](https://mlsanity.com/paper/2102.04257/) (2021)
- [The Edinburgh International Accents of English Corpus: Towards the Democratization of English ASR](https://mlsanity.com/paper/2303.18110/) (2023)
- [Queer In AI: A Case Study in Community-Led Participatory AI](https://mlsanity.com/paper/2303.16972/) (2023)
- [Towards measuring fairness in speech recognition: Fair-Speech dataset](https://mlsanity.com/paper/2408.12734/) (2024)
- [Twists, Humps, and Pebbles: Multilingual Speech Recognition Models Exhibit Gender Performance Gaps](https://mlsanity.com/paper/2402.17954/) (2024)
- [Gender Representation in French Broadcast Corpora and Its Impact on ASR Performance](https://mlsanity.com/paper/1908.08717/) (2019)
- [Augmented Datasheets for Speech Datasets and Ethical Decision-Making](https://mlsanity.com/paper/2305.04672/) (2023)
- [Pre-trained Speech Processing Models Contain Human-Like Biases that Propagate to Speech Emotion Recognition](https://mlsanity.com/paper/2310.18877/) (2023)
- [1000 African Voices: Advancing inclusive multi-speaker multi-accent speech synthesis](https://mlsanity.com/paper/2406.11727/) (2024)
- [Beyond the binary: Limitations and possibilities of gender-related speech technology research](https://mlsanity.com/paper/2409.13335/) (2024)
- [Promoting the Responsible Development of Speech Datasets for Mental Health and Neurological Disorders Research](https://mlsanity.com/paper/2406.04116/) (2024)
- [On the Role of Speech Data in Reducing Toxicity Detection Bias](https://mlsanity.com/paper/2411.08135/) (2024)
- [Reclaiming Power over AI: Equipping Queer Teens as AI Designers for HIV Prevention](https://mlsanity.com/paper/2406.13018/) (2024)
- [Speech After Gender: A Trans-Feminine Perspective on Next Steps for Speech Science and Technology](https://mlsanity.com/paper/2407.07235/) (2024)

## Abstract (arXiv)

In this paper, we motivate the need for a participatory speech dataset creation framework through a case study of the LGBTQIA+, or queer, community - a community with documented concerns about AI and reported harms, including attempts to develop 'gaydar' technologies that purportedly identify individuals as queer. We review common speech data collection practices, why these methods may be unsuitable for engaging with queer speakers, and discuss previous efforts in participatory AI with queer community engagement, as well as participatory endeavours specific to speech data collection for other marginalized communities. From this review, we develop a conceptual framework for participatory speech data curation by, for, and with marginalized communities drawing on insights from co-design and knowledge sharing. We propose a framework comprising overlapping and two-way processes of defining a community, project formulation, modes of participation, and personal autonomy.