Abstract
The Helsinki-NLP team participated in the NADI 2023 shared tasks on Arabic dialect translation with seven submissions. We used statistical (SMT) and neural machine translation (NMT) methods and explored character- and subword-based data preprocessing. Our submissions placed second in both tracks. In the open track, our winning submission is a character-level SMT system with additional Modern Standard Arabic language models. In the closed track, our best BLEU scores were obtained with the leave-as-is baseline, a simple copy of the input, and narrowly followed by SMT systems. In both tracks, fine-tuning existing multilingual models such as AraT5 or ByT5 did not yield superior performance compared to SMT.- Anthology ID:
- 2023.arabicnlp-1.73
- 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:
- SIGARAB
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 670–677
- Language:
- URL:
- https://preview.aclanthology.org/add_missing_videos/2023.arabicnlp-1.73/
- DOI:
- 10.18653/v1/2023.arabicnlp-1.73
- Cite (ACL):
- Yves Scherrer, Aleksandra Miletić, and Olli Kuparinen. 2023. The Helsinki-NLP Submissions at NADI 2023 Shared Task: Walking the Baseline. In Proceedings of ArabicNLP 2023, pages 670–677, Singapore (Hybrid). Association for Computational Linguistics.
- Cite (Informal):
- The Helsinki-NLP Submissions at NADI 2023 Shared Task: Walking the Baseline (Scherrer et al., ArabicNLP 2023)
- PDF:
- https://preview.aclanthology.org/add_missing_videos/2023.arabicnlp-1.73.pdf