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Taking MT Evaluation Metrics to Extremes: Beyond Correlation with Human Judgments
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In: Computational Linguistics, Vol 45, Iss 3, Pp 515-558 (2019) (2019)
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The Role of human reference translation in machine translation evaluation
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In: TDX (Tesis Doctorals en Xarxa) (2017)
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USFD at SemEval-2016 task 1: putting different state-of-the-arts into a box
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In: 609 ; 613 (2016)
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Análisis del tratamiento de la terminología en la traducción automática: implicaciones para la evaluación
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In: Debate Terminológico; n. 10 (2013) ; Debate Terminológico. ISSN: 1813-1867; n. 10 (2013) ; 1813-1867 (2013)
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UPF-cobalt submission to WMT15 metrics task
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Abstract:
Comunicació presentada a: 10th Workshop on Statistical Machine Translation, celebrat a Lisboa, Portugal, del 17 al 18 de setembre de 2015. ; An important limitation of automatic evaluation metrics is that, when comparing Machine Translation (MT) to a human reference, they are often unable to discriminate between acceptable variation and the differences that are indicative of MT errors. In this paper we present UPF-Cobalt evaluation system that addresses this issue by penalizing the differences in the syntactic contexts of aligned candidate and reference words. We evaluate our metric using the data from WMT workshops of the recent years and show that it performs competitively both at segment and at system levels. ; This work was supported by IULA (UPF) and the FIDGR grant program of the Generalitat de Catalunya.
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Keyword:
Evaluation metrics; Statistical Machine Translation
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URL: http://hdl.handle.net/10230/36827
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