The Esethu Framework: Reimagining Sustainable Dataset Governance and Curation for Low-Resource Languages
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| Autores principales: | , , , , , , , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866913889869889536 |
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| author | Rajab, Jenalea Aremu, Anuoluwapo Chimoto, Everlyn Asiko Dunbar, Dale Morrissey, Graham Thior, Fadel Potgieter, Luandrie Ojo, Jessico Tonja, Atnafu Lambebo Chetty, Maushami Nekoto, Wilhelmina NdapewaOnyothi Moiloa, Pelonomi Abbott, Jade Marivate, Vukosi Rosman, Benjamin |
| author_facet | Rajab, Jenalea Aremu, Anuoluwapo Chimoto, Everlyn Asiko Dunbar, Dale Morrissey, Graham Thior, Fadel Potgieter, Luandrie Ojo, Jessico Tonja, Atnafu Lambebo Chetty, Maushami Nekoto, Wilhelmina NdapewaOnyothi Moiloa, Pelonomi Abbott, Jade Marivate, Vukosi Rosman, Benjamin |
| contents | This paper presents the Esethu Framework, a sustainable data curation framework specifically designed to empower local communities and ensure equitable benefit-sharing from their linguistic resource. This framework is supported by the Esethu license, a novel community-centric data license. As a proof of concept, we introduce the Vuk'uzenzele isiXhosa Speech Dataset (ViXSD), an open-source corpus developed under the Esethu Framework and License. The dataset, containing read speech from native isiXhosa speakers enriched with demographic and linguistic metadata, demonstrates how community-driven licensing and curation principles can bridge resource gaps in automatic speech recognition (ASR) for African languages while safeguarding the interests of data creators. We describe the framework guiding dataset development, outline the Esethu license provisions, present the methodology for ViXSD, and present ASR experiments validating ViXSD's usability in building and refining voice-driven applications for isiXhosa. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_15916 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | The Esethu Framework: Reimagining Sustainable Dataset Governance and Curation for Low-Resource Languages Rajab, Jenalea Aremu, Anuoluwapo Chimoto, Everlyn Asiko Dunbar, Dale Morrissey, Graham Thior, Fadel Potgieter, Luandrie Ojo, Jessico Tonja, Atnafu Lambebo Chetty, Maushami Nekoto, Wilhelmina NdapewaOnyothi Moiloa, Pelonomi Abbott, Jade Marivate, Vukosi Rosman, Benjamin Computation and Language This paper presents the Esethu Framework, a sustainable data curation framework specifically designed to empower local communities and ensure equitable benefit-sharing from their linguistic resource. This framework is supported by the Esethu license, a novel community-centric data license. As a proof of concept, we introduce the Vuk'uzenzele isiXhosa Speech Dataset (ViXSD), an open-source corpus developed under the Esethu Framework and License. The dataset, containing read speech from native isiXhosa speakers enriched with demographic and linguistic metadata, demonstrates how community-driven licensing and curation principles can bridge resource gaps in automatic speech recognition (ASR) for African languages while safeguarding the interests of data creators. We describe the framework guiding dataset development, outline the Esethu license provisions, present the methodology for ViXSD, and present ASR experiments validating ViXSD's usability in building and refining voice-driven applications for isiXhosa. |
| title | The Esethu Framework: Reimagining Sustainable Dataset Governance and Curation for Low-Resource Languages |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2502.15916 |