Abstract
Cantonese, the second most prevalent Chinese dialect after Mandarin, has been relatively overlooked in machine translation (MT) due to a scarcity of bilingual resources. In this paper, we propose to leverage Mandarin, a high-resource language, as a pivot language for translating between Cantonese and English. Our method utilizes transfer learning from pre-trained Bidirectional and Auto-Regressive Transformer (BART) models to initialize auxiliary source-pivot and pivot-target MT models. The parameters of the trained auxiliary models are then used to initialize the source-target model. Based on our experiments, our proposed method outperforms several baseline initialization strategies, naive pivot translation, and two commercial translation systems in both translation directions.- Anthology ID:
- 2024.loresmt-1.8
- Volume:
- Proceedings of the The Seventh Workshop on Technologies for Machine Translation of Low-Resource Languages (LoResMT 2024)
- Month:
- August
- Year:
- 2024
- Address:
- Bangkok, Thailand
- Editors:
- Atul Kr. Ojha, Chao-hong Liu, Ekaterina Vylomova, Flammie Pirinen, Jade Abbott, Jonathan Washington, Nathaniel Oco, Valentin Malykh, Varvara Logacheva, Xiaobing Zhao
- Venues:
- LoResMT | WS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 74–84
- Language:
- URL:
- https://aclanthology.org/2024.loresmt-1.8
- DOI:
- Cite (ACL):
- King Yiu Suen, Rudolf Chow, and Albert Y.S. Lam. 2024. Leveraging Mandarin as a Pivot Language for Low-Resource Machine Translation between Cantonese and English. In Proceedings of the The Seventh Workshop on Technologies for Machine Translation of Low-Resource Languages (LoResMT 2024), pages 74–84, Bangkok, Thailand. Association for Computational Linguistics.
- Cite (Informal):
- Leveraging Mandarin as a Pivot Language for Low-Resource Machine Translation between Cantonese and English (Suen et al., LoResMT-WS 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2024.loresmt-1.8.pdf