Results of the WMT19 metrics shared task: segment-level and strong MT systems pose big challenges
Ma, Qingsong, Wei, Johnny Tian-Zheng, Bojar, OndřejORCID: 0000-0002-0606-0050 and Graham, Yvette
(2019)
Results of the WMT19 metrics shared task: segment-level and strong MT systems pose big challenges.
In: Fourth Conference on Machine Translation, 1-2 Aug 2019, Florence, Italy.
This paper presents the results of the WMT19 Metrics Shared Task. Participants were asked to score the outputs of the translations systems competing in the WMT19 News Translation Task with automatic metrics. 13 research groups submitted 24 metrics, 10 of which are reference-less "metrics" and constitute submissions to the joint task with WMT19 Quality Estimation Task, "QE as a Metric". In addition, we computed 11 baseline metrics, with 8 commonly applied baselines (BLEU, SentBLEU, NIST, WER, PER, TER, CDER, and chrF) and 3 reimplementations (chrF+, sacreBLEU-BLEU, and sacreBLEU-chrF). Metrics were evaluated on the system level, how well a given metric correlates with the WMT19 official manual ranking, and segment level, how well the metric correlates with human judgements of segment quality. This year, we use direct assessment (DA) as our only form of manual evaluation.
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Funders:
Czech Science Foundation grant 19-26934X (NEUREM3), Science Foundation Ireland (SFI) Research Centres Programme (Grant 13/RC/2106), European Regional Development Fund, Charles University Research Programme “Progres” Q18+Q48
ID Code:
24262
Deposited On:
06 Mar 2020 10:15 by
Yvette Graham
. Last Modified 25 Nov 2020 14:34