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The SADID Evaluation Datasets for Low-Resource Spoken Language Machine Translation of Arabic Dialects

Wael Abid
2020 Proceedings of the 28th International Conference on Computational Linguistics   unpublished

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Low-resource Machine Translation recently gained a lot of popularity, and for certain languages, it has made great strides. However, it is still difficult to track progress in other languages for which there is no publicly available evaluation data. In this paper, we introduce benchmark datasets for Arabic and its dialects. We describe our design process and motivations and analyze the datasets to understand their resulting properties. Numerous successful attempts use large monolingual corpora
more » ... o augment low-resource pairs. We try to approach augmentation differently and investigate whether it is possible to improve MT models without any external sources of data. We accomplish this by bootstrapping existing parallel sentences and complement this with multilingual training to achieve strong baselines. 2 Related Work Machine Translation resources for Arabic are mostly focused on MSA. Nonetheless, there are a number of efforts dedicated to dialects. The BOLT (Broad Operational Language Translation) 1 program This work is licensed under a Creative Commons Attribution 4.0 International License. License details:
doi:10.18653/v1/2020.coling-main.530 fatcat:vxrsok7rpndzpoz46fnxvkss3e
Citation

Wael Abid. "The SADID Evaluation Datasets for Low-Resource Spoken Language Machine Translation of Arabic Dialects." Proceedings of the 28th International Conference on Computational Linguistics (2020)