Abstract
In this paper, we present our findings within the context of the NADI-2023 Shared Task (Subtask 2). Our task involves developing a translation model from the Palestinian, Jordanian, Emirati, and Egyptian dialects to Modern Standard Arabic (MSA) using the MADAR parallel corpus, even though it lacks a parallel subset for the Emirati dialect. To address this challenge, we conducted a comparative analysis, evaluating the fine-tuning results of various transformer models using the MADAR corpus as a learning resource. Additionally, we assessed the effectiveness of existing translation tools in achieving our translation objectives. The best model achieved a BLEU score of 11.14% on the dev set and 10.02 on the test set.- Anthology ID:
- 2023.arabicnlp-1.75
- Volume:
- Proceedings of ArabicNLP 2023
- Month:
- December
- Year:
- 2023
- Address:
- Singapore (Hybrid)
- Editors:
- Hassan Sawaf, Samhaa El-Beltagy, Wajdi Zaghouani, Walid Magdy, Ahmed Abdelali, Nadi Tomeh, Ibrahim Abu Farha, Nizar Habash, Salam Khalifa, Amr Keleg, Hatem Haddad, Imed Zitouni, Khalil Mrini, Rawan Almatham
- Venues:
- ArabicNLP | WS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 683–689
- Language:
- URL:
- https://aclanthology.org/2023.arabicnlp-1.75
- DOI:
- 10.18653/v1/2023.arabicnlp-1.75
- Cite (ACL):
- Wiem Derouich, Sameh Kchaou, and Rahma Boujelbane. 2023. ANLP-RG at NADI 2023 shared task: Machine Translation of Arabic Dialects: A Comparative Study of Transformer Models. In Proceedings of ArabicNLP 2023, pages 683–689, Singapore (Hybrid). Association for Computational Linguistics.
- Cite (Informal):
- ANLP-RG at NADI 2023 shared task: Machine Translation of Arabic Dialects: A Comparative Study of Transformer Models (Derouich et al., ArabicNLP-WS 2023)
- PDF:
- https://preview.aclanthology.org/ingest-2024-clasp/2023.arabicnlp-1.75.pdf