Please use this identifier to cite or link to this item: http://hdl.handle.net/10609/151238
Title: PE effort and neural-based automatic MT metrics: do they correlate?
Author: Oliver, Antoni  
Alvarez Vidal, Sergi  
Citation: Alvarez-Vidal, S. [Sergi] & Oliver, A. [Antoni]. (2023). PE effort and neural-based automatic MT metrics: do they correlate?. Proceedings of the 24th Annual Conference of the European Association for Machine Translation
Abstract: Neural machine translation (NMT) has shown overwhelmingly good results in recent times. This improvement in quality has boosted the presence of NMT in nearly all fields of translation. Most current translation industry workflows include postediting (PE) of MT as part of their process. For many domains and language combinations, translators post-edit raw machine translation (MT) to produce the final document. However, this process can only work properly if the quality of the raw MT output can be assured. MT is usually evaluated using automatic scores, as they are much faster and cheaper. However, traditional automatic scores have not been good quality indicators and do not correlate with PE effort. We analyze the correlation of each of the three dimensions of PE effort (temporal, technical and cognitive) with COMET, a neural framework which has obtained outstanding results in recent MT evaluation campaigns.
Document type: info:eu-repo/semantics/conferenceObject
Issue Date: Jun-2023
Publication license: http://creativecommons.org/licenses/by-nd/3.0/es/  
Appears in Collections:Conferencias

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