Related papers: Survey of Low-Resource Machine Translation

Survey of Low-Resource Machine Translation

URL: http://arxiv.org/abs/2109.00486v1
Date: Wed, 1 Sep 2021 16:57:58 GMT
Title: Survey of Low-Resource Machine Translation
Authors: Barry Haddow, Rachel Bawden, Antonio Valerio Miceli Barone, Jind\v{r}ich Helcl, Alexandra Birch
Abstract summary: 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.
Score: 65.52755521004794
License: http://creativecommons.org/licenses/by/4.0/
Abstract: We present a survey covering the state of the art in low-resource machine translation. 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 high level summary of this topical field and provide an overview of best practices.

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