Accent Classification is Challenging but Pre-training Helps: a case study with novel Brazilian Portuguese datasets
Ariadne Matos, Gustavo Araújo, Arnaldo Candido Junior, Moacir Ponti
- Anthology ID:
- 2024.propor-1.37
- Volume:
- Proceedings of the 16th International Conference on Computational Processing of Portuguese - Vol. 1
- Month:
- March
- Year:
- 2024
- Address:
- Santiago de Compostela, Galicia/Spain
- Editors:
- Pablo Gamallo, Daniela Claro, António Teixeira, Livy Real, Marcos Garcia, Hugo Gonçalo Oliveira, Raquel Amaro
- Venue:
- PROPOR
- SIG:
- Publisher:
- Association for Computational Lingustics
- Note:
- Pages:
- 364–373
- Language:
- URL:
- https://aclanthology.org/2024.propor-1.37
- DOI:
- Cite (ACL):
- Ariadne Matos, Gustavo Araújo, Arnaldo Candido Junior, and Moacir Ponti. 2024. Accent Classification is Challenging but Pre-training Helps: a case study with novel Brazilian Portuguese datasets. In Proceedings of the 16th International Conference on Computational Processing of Portuguese - Vol. 1, pages 364–373, Santiago de Compostela, Galicia/Spain. Association for Computational Lingustics.
- Cite (Informal):
- Accent Classification is Challenging but Pre-training Helps: a case study with novel Brazilian Portuguese datasets (Matos et al., PROPOR 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2024.propor-1.37.pdf