Montreal Neural Machine Translation Systems for WMT'15.

WMT@EMNLP(2015)

引用 182|浏览292
暂无评分
摘要
Neural machine translation (NMT) systems have recently achieved results comparable to the state of the art on a few translation tasks, including English→French and English→German. The main purpose of the Montreal Institute for Learning Algorithms (MILA) submission to WMT’15 is to evaluate this new approach on a greater variety of language pairs. Furthermore, the human evaluation campaign may help us and the research community to better understand the behaviour of our systems. We use the RNNsearch architecture, which adds an attention mechanism to the encoderdecoder. We also leverage some of the recent developments in NMT, including the use of large vocabularies, unknown word replacement and, to a limited degree, the inclusion of monolingual language models.
更多
查看译文
关键词
Machine translation,Language model,Natural language processing,Artificial intelligence,Computer science,Leverage (statistics),Architecture,Research community
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要