NMTPY: A Flexible Toolkit for Advanced Neural Machine Translation Systems

Abstract In this paper, we present nmtpy, a flexible Python toolkit based on Theano for training Neural Machine Translation and other neural sequence-to-sequence architectures. nmtpy decouples the specification of a network from the training and inference utilities to simplify the addition of a new architecture and reduce the amount of boilerplate code to be written. nmtpy has been used for LIUM’s top-ranked submissions to WMT Multimodal Machine Translation and News Translation tasks in 2016 and 2017.

• Publication year

  2017

• Venue

  Prague Bulletin of Mathematical Linguistics

• Publication date

  2017-06-01

• Fields of study

  Mathematics, Linguistics, Computer Science

• Identifiers
  DOI 10.1515/pralin-2017-0035arXiv 1706.00457
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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