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 | Artificial Intelligence |
| 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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