Name: The SADID Evaluation Datasets 
Description: Evaluation Datasets for Low-Resource Spoken Language Machine Translation of Arabic Dialects
Provider: Stanford University
Paper Title: The SADID Evaluation Datasets for Low-Resource Spoken Language
  Machine Translation of Arabic Dialects
Tasks: machine translation
Venue Name: International Conference on Computational Linguistics
Authors: Wael Abid
Abstract: 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 to 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.