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arXiv · 2004.05219

Joint translation and unit conversion for end-to-end localization

Georgiana Dinu·Prashant Mathur·Marcello Federico·Stanislas Lauly·Yaser Al-Onaizan
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Abstract

A variety of natural language tasks require processing of textual data which contains a mix of natural language and formal languages such as mathematical expressions. In this paper, we take unit conversions as an example and propose a data augmentation technique which leads to models learning both translation and conversion tasks as well as how to adequately switch between them for end-to-end localization.

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Georgiana Dinu, Prashant Mathur, Marcello Federico, Stanislas Lauly, Yaser Al-Onaizan. 2020-04-10. Joint translation and unit conversion for end-to-end localization. https://arxiv.org/abs/2004.05219

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