Why not be Versatile? Applications of the SGNMT Decoder for Machine Translation
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Authors
Iglesias, Gonzalo
Byrne, WJ
Abstract
SGNMT is a decoding platform for machine translation which allows paring various modern neural models of translation with different kinds of constraints and symbolic models. In this paper, we describe three use cases in which SGNMT is currently playing an active role: (1) teaching as SGNMT is being used for course work and student theses in the MPhil in Machine Learning, Speech and Language Technology at the University of Cambridge, (2) research as most of the research work of the Cambridge MT group is based on SGNMT, and (3) technology transfer as we show how SGNMT is helping to transfer research findings from the laboratory to the industry, eg. into a product of SDL plc.
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Keywords
cs.CL, cs.CL
Journal Title
AMTA 2018
Conference Name
13th biennial conference of the Association for Machine Translation in the Americas (AMTA 2018)
Journal ISSN
Volume Title
1
Publisher
AMTA
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Sponsorship
EPSRC (1632937)