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:
Bibkey:
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)
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PDF:
https://aclanthology.org/2024.propor-1.37.pdf