Findings of the Second Workshop on Neural Machine Translation and Generation
Autor: | Graham Neubig, Alexandra Birch, Yusuke Oda, Andrew Finch, Minh-Thang Luong |
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Rok vydání: | 2018 |
Předmět: |
FOS: Computer and information sciences
Structure (mathematical logic) Computer Science - Computation and Language Machine translation Computer science business.industry Association (object-oriented programming) 05 social sciences 010501 environmental sciences computer.software_genre 01 natural sciences Task (project management) 0502 economics and business Artificial intelligence 050207 economics Computational linguistics business Computation and Language (cs.CL) computer Natural language processing 0105 earth and related environmental sciences |
Zdroj: | NMT@ACL |
Popis: | This document describes the findings of the Second Workshop on Neural Machine Translation and Generation, held in concert with the annual conference of the Association for Computational Linguistics (ACL 2018). First, we summarize the research trends of papers presented in the proceedings, and note that there is particular interest in linguistic structure, domain adaptation, data augmentation, handling inadequate resources, and analysis of models. Second, we describe the results of the workshop's shared task on efficient neural machine translation, where participants were tasked with creating MT systems that are both accurate and efficient. Comment: WNMT 2018 |
Databáze: | OpenAIRE |
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