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LAYERED: Metric for Machine Translation Evaluation

机译:分层:机器翻译评估的指标

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This paper describes the LAYERED metric which is used for the shared WMT'14 metrics task. Various metrics exist for MT evaluation: BLEU (Papineni, 2002), METEOR (Alon Lavie, 2007), TER (Snover, 2006) etc., but are found inadequate in quite a few language settings like, for example, in case of free word order languages. In this paper, we propose an MT evaluation scheme that is based on the NLP layers: lexical, syntactic and semantic. We contend that higher layer metrics are after all needed. Results are presented on the corpora of ACL-WMT, 2013 and 2014. We end with a metric which is composed of weighted metrics at individual layers, which correlates very well with human judgment.
机译:本文介绍了用于共享WMT'14指标任务的LAYERED指标。 MT评估有多种度量标准:BLEU(Papineni,2002),METEOR(Alon Lavie,2007),TER(Snover,2006)等,但是在相当多的语言设置中都不够用,例如免费时单词顺序语言。在本文中,我们提出了一种基于词法,句法和语义等NLP层的MT评估方案。我们认为,毕竟需要更高的层度量。结果在ACL-WMT的语料库(2013年和2014年)上进行了介绍。我们以一个度量标准结尾,该度量标准由各个层级的加权度量标准组成,与人类的判断力非常相关。

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