Investigating an Approach for Low Resource Language Dataset Creation, Curation and Classification: Setswana and Sepedi
Vukosi Marivate, Tshephisho Sefara, Vongani Chabalala, Keamogetswe Makhaya, Tumisho Mokgonyane, Rethabile Mokoena, Abiodun Modupe
Abstract
The recent advances in Natural Language Processing have only been a boon for well represented languages, negating research in lesser known global languages. This is in part due to the availability of curated data and research resources. One of the current challenges concerning low-resourced languages are clear guidelines on the collection, curation and preparation of datasets for different use-cases. In this work, we take on the task of creating two datasets that are focused on news headlines (i.e short text) for Setswana and Sepedi and the creation of a news topic classification task from these datasets. In this study, we document our work, propose baselines for classification, and investigate an approach on data augmentation better suited to low-resourced languages in order to improve the performance of the classifiers.- Anthology ID:
- 2020.rail-1.3
- Volume:
- Proceedings of the first workshop on Resources for African Indigenous Languages
- Month:
- May
- Year:
- 2020
- Address:
- Marseille, France
- Editors:
- Rooweither Mabuya, Phathutshedzo Ramukhadi, Mmasibidi Setaka, Valencia Wagner, Menno van Zaanen
- Venue:
- RAIL
- SIG:
- Publisher:
- European Language Resources Association (ELRA)
- Note:
- Pages:
- 15–20
- Language:
- English
- URL:
- https://aclanthology.org/2020.rail-1.3
- DOI:
- Cite (ACL):
- Vukosi Marivate, Tshephisho Sefara, Vongani Chabalala, Keamogetswe Makhaya, Tumisho Mokgonyane, Rethabile Mokoena, and Abiodun Modupe. 2020. Investigating an Approach for Low Resource Language Dataset Creation, Curation and Classification: Setswana and Sepedi. In Proceedings of the first workshop on Resources for African Indigenous Languages, pages 15–20, Marseille, France. European Language Resources Association (ELRA).
- Cite (Informal):
- Investigating an Approach for Low Resource Language Dataset Creation, Curation and Classification: Setswana and Sepedi (Marivate et al., RAIL 2020)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2020.rail-1.3.pdf