Survey of Low-Resource Machine Translation
It provides a comprehensive overview for researchers working on translation in languages with limited data, but it is incremental as it synthesizes existing work.
This survey addresses the challenge of machine translation for low-resource languages, summarizing state-of-the-art techniques and evaluations from recent shared tasks.
We present a survey covering the state of the art in low-resource machine translation research. There are currently around 7000 languages spoken in the world and almost all language pairs lack significant resources for training machine translation models. There has been increasing interest in research addressing the challenge of producing useful translation models when very little translated training data is available. We present a summary of this topical research field and provide a description of the techniques evaluated by researchers in several recent shared tasks in low-resource MT.