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Results of the WMT17 Metrics Shared Task

机译:WMT17指标共享任务的结果

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This paper presents the results of the WMT17 Metrics Shared Task. We asked participants of this task to score the outputs of the MT systems involved in the WMT17 news translation task and Neural MT training task. We collected scores of 14 metrics from 8 research groups. In addition to that, we computed scores of 7 standard metrics (BLEU, SentBLEU, NIST, WER, PER, TER and CDER) as baselines. The collected scores were evaluated in terms of system-level correlation (how well each metnc's scores correlate with WMT17 official manual ranking of systems) and in terms of segment level correlation (how often a metric agrees with humans in judging the quality of a particular sentence). This year, we build upon two types of manual judgements: direct assessment (DA) and HUME manual semantic judgements.
机译:本文介绍了WMT17指标共享任务的结果。我们要求此任务的参与者对参与WMT17新闻翻译任务和神经MT培训任务的MT系统的输出进行评分。我们从8个研究小组中收集了14个指标的得分。除此之外,我们还计算了7个标准指标(BLEU,SentBLEU,NIST,WER,PER,TER和CDER)的分数作为基线。收集的分数是根据系统级别的相关性(每个metnc的分数与WMT17官方手册对系统的排名的相关性)和段级别的相关性(度量标准在判断特定句子的质量时与人一致的频率)进行评估的)。今年,我们基于两种类型的手动判断:直接评估(DA)和HUME手动语义判断。

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