Detecting Loanwords in Emakhuwa: An Extremely Low-Resource Bantu Language Exhibiting Significant Borrowing from Portuguese
Felermino Dario Mario Ali, Henrique Lopes Cardoso, Rui Sousa-Silva
Abstract
The accurate identification of loanwords within a given text holds significant potential as a valuable tool for addressing data augmentation and mitigating data sparsity issues. Such identification can improve the performance of various natural language processing tasks, particularly in the context of low-resource languages that lack standardized spelling conventions.This research proposes a supervised method to identify loanwords in Emakhuwa, borrowed from Portuguese. Our methodology encompasses a two-fold approach. Firstly, we employ traditional machine learning algorithms incorporating handcrafted features, including language-specific and similarity-based features. We build upon prior studies to extract similarity features and propose utilizing two external resources: a Sequence-to-Sequence model and a dictionary. This innovative approach allows us to identify loanwords solely by analyzing the target word without prior knowledge about its donor counterpart. Furthermore, we fine-tune the pre-trained CANINE model for the downstream task of loanword detection, which culminates in the impressive achievement of the F1-score of 93%. To the best of our knowledge, this study is the first of its kind focusing on Emakhuwa, and the preliminary results are promising as they pave the way to further advancements.- Anthology ID:
- 2024.lrec-main.425
- Volume:
- Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
- Month:
- May
- Year:
- 2024
- Address:
- Torino, Italia
- Editors:
- Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue
- Venues:
- LREC | COLING
- SIG:
- Publisher:
- ELRA and ICCL
- Note:
- Pages:
- 4750–4759
- Language:
- URL:
- https://aclanthology.org/2024.lrec-main.425
- DOI:
- Cite (ACL):
- Felermino Dario Mario Ali, Henrique Lopes Cardoso, and Rui Sousa-Silva. 2024. Detecting Loanwords in Emakhuwa: An Extremely Low-Resource Bantu Language Exhibiting Significant Borrowing from Portuguese. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 4750–4759, Torino, Italia. ELRA and ICCL.
- Cite (Informal):
- Detecting Loanwords in Emakhuwa: An Extremely Low-Resource Bantu Language Exhibiting Significant Borrowing from Portuguese (Ali et al., LREC-COLING 2024)
- PDF:
- https://preview.aclanthology.org/add_acl24_videos/2024.lrec-main.425.pdf