Results 11 to 20 of about 6,139,878 (265)
Pauses as Indicators of Cognitive Effort in Post-editing Machine Translation Output [PDF]
Across Languages and Cultures, 2006 In translation process and language production research, pauses are seen as indicators of cognitive processing. Investigating the correlations between source text machine translatability and post-editing effort involves an assessment of cognitive effort. Therefore, an analysis of pauses is essential.
O'Brien, Sharon, O\u27Brien, Sharon
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SAGE OpenMachine translation post-editing (MTPE) is a process where humans and machines meet. While previous researchers have adopted psychological and cognitive approaches to explore the factors affecting MTPE performance, little research has been carried out to
Xinyang Peng, Xiangling Wang, Xiaoye Li
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Translation Quality and Error Recognition in Professional Neural Machine Translation Post-Editing
Informatics, 2019 This study aims to analyse how translation experts from the German department of the European Commission’s Directorate-General for Translation (DGT) identify and correct different error categories in neural machine translated texts (NMT) and their ...
Jennifer Vardaro +2 more
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, 2017 Post-editing of machine translation (MT) is now increasingly implemented in the human translation workflow after studies in both industry and academia have demonstrated the efficacy of this practice. Post-editing still involves open questions, however, such as how best to train post-editors and how to estimate the effort required by post-editing tasks.
Vieira, Lucas N
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Eye tracking as a measure of cognitive effort for post-editing of machine translation [PDF]
, 2018 Abstract The three measurements for post-editing effort as proposed by Krings (2001) have been adopted by many researchers in subsequent studies and publications. These measurements comprise temporal effort (the speed or productivity rate of post-editing, often measured in words per second at the segment level), technical effort (the number of actual ...
Joss Moorkens, Moorkens, Joss
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Assessing Post-editing Effort in the English-Hindi Direction
CoRR, 2021 ICON ...
Arafat Ahsan +2 more
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Effort-Aware Neural Automatic Post-Editing [PDF]
Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2), 2019 For this round of the WMT 2019 APE shared task, our submission focuses on addressing the “over-correction” problem in APE. Over-correction occurs when the APE system tends to rephrase an already correct MT output, and the resulting sentence is penalized by a reference-based evaluation against human post-edits.
Amirhossein Tebbifakhr +2 more
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Assessing MT with measures of PE effort
Ampersand, 2023 Recent improvements in quality obtained by neural machine translation (NMT) have boosted its presence in the translation industry. In many domains and language combinations, translators post-edit raw MT output: they edit and correct the pre-translated ...
Sergi Alvarez-Vidal, Antoni Oliver
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Differentiating editing, post-editing, and revision [PDF]
, 2020 While several studies report translator resistance to post-editing, translators whose work has followed the evolution of translation technology may consider post-editing to be translation with just another input.
Moorkens, Joss, do Carmo, Félix
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Post-Editing in Practice: Process, Product and Networks
, 2019 The potential benefits of integrating machine translation into human translation workflows are now widely recognised. In many sectors of the translation industry, translators’ throughput is improved with the use of machine translation as a tool in the ...
Alonso, E., Nunes Vieira, L., Bywood, L.
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