XNMT: The eXtensible Neural Machine Translation Toolkit

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Authors John Hewitt, Matthias Sperber, Rachid Riad, Graham Neubig, Ye Qi, Austin Matthews, Philip Arthur, Xinyi Wang, Sarguna Padmanabhan, Liming Wang, Devendra Singh Sachan, Matthieu Felix, Pierre Godard
Journal/Conference Name WS 2018 3
Paper Category
Paper Abstract This paper describes XNMT, the eXtensible Neural Machine Translation toolkit. XNMT distin- guishes itself from other open-source NMT toolkits by its focus on modular code design, with the purpose of enabling fast iteration in research and replicable, reliable results. In this paper we describe the design of XNMT and its experiment configuration system, and demonstrate its utility on the tasks of machine translation, speech recognition, and multi-tasked machine translation/parsing. XNMT is available open-source at https://github.com/neulab/xnmt
Date of publication 2018
Code Programming Language Python
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