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Montreal Neural Machine Translation Systems for WMT'15

机译:适用于WMT'15的蒙特利尔神经机器翻译系统

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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 encoder-decoder. 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.
机译:神经机器翻译(NMT)系统最近在一些翻译任务(包括英语→法语和英语→德语)上取得了与现有技术相当的结果。蒙特利尔学习算法研究所(MILA)向WMT'15提交的主要目的是在更多种语言对上评估这种新方法。此外,人类评估活动可以帮助我们和研究界更好地了解我们系统的行为。我们使用RNNsearch架构,该架构为编码器-解码器添加了一种关注机制。我们还利用了NMT的一些最新发展,包括使用大量词汇,未知单词替换以及在一定程度上包括单语种语言模型。

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