The efficacy of human post-editing for language translation

@article{Green2013TheEO,
  title={The efficacy of human post-editing for language translation},
  author={Spence Green and Jeffrey Heer and Christopher D. Manning},
  journal={Proceedings of the SIGCHI Conference on Human Factors in Computing Systems},
  year={2013}
}
Language translation is slow and expensive, so various forms of machine assistance have been devised. Automatic machine translation systems process text quickly and cheaply, but with quality far below that of skilled human translators. To bridge this quality gap, the translation industry has investigated post-editing, or the manual correction of machine output. We present the first rigorous, controlled analysis of post-editing and find that post-editing leads to reduced time and, surprisingly… 
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References

SHOWING 1-10 OF 61 REFERENCES
A process study of computer-aided translation
TLDR
The computer-aided tool Caitra is developed that makes suggestions for sentence completion, shows word and phrase translation options, and allows postediting of machine translation output.
Translating by post-editing: is it the way forward?
  • I. Garcia
  • Computer Science
    Machine Translation
  • 2011
TLDR
It is discussed whether translators should consider post-editing as a viable alternative to conventional translation, as it produces significantly better statistical results compared to translating manually.
Repairing Texts: Empirical Investigations of Machine Translation Post-Editing Processes
TLDR
In Repairing Texts, Hans P. Krings challenges the idea that, given the effectiveness of machine translation, major costs could be reduced by using monolingual staff to post -- edit translations.
Post-editing machine translated text in a commercial setting: Observation and statistical analysis
TLDR
A mixed method approach was employed to both quantitatively and qualitatively analyse the data and gain detailed insights into the post-editing activity from various view points, indicating that a number of factors, such as sentence structure, document component types, use of product specific terms, and post-edsiting patterns and behaviour, have effect on the amount of post-EDiting effort in an intertwined manner.
Pauses as Indicators of Cognitive Effort in Post-editing Machine Translation Output
TLDR
This paper presents data from a research project which includes an analysis of pauses in post-editing, triangulated with the Choice Network Analysis method and Translog, and suggests that while pauses provide some indication of cognitive processing, supplementary methods are required to give a fuller picture.
A Productivity Test of Statistical Machine Translation Post-Editing in a Typical Localisation Context
TLDR
A Productivity Test of Statistical Machine Translation Post-Editing in a Typical Localisation Context and results show a productivity increase for each participant, with significant variance across inviduals.
Enabling Monolingual Translators: Post-Editing vs. Options
TLDR
This study carried out a study on monolingual translators with no knowledge of the source language, but aided by post-editing and the display of translation options, able to translate 35% of Arabic and 28% of Chinese sentences correctly on average.
Collaborative translation by monolinguals with machine translators
In this paper, we present the concept for collaborative translation, where two non-bilingual people who use different languages collaborate to perform the task of translation using machine
Interactive translation vs pre-translation in the context of translation memory systems: Investigating the effects of translation method on productivity, quality and translator satisfaction
TLDR
As the demand for translation continues to rise, more and more translators are looking to TMs to help increase productivity; however, for a variety of reasons, such as cost and incompatible file formats, they do not always have access to a useful TM.
Long Distance Revisions in Drafting and Post-editing
TLDR
Property of translation processes, as observed in the translation behaviour of student and professional translators, are investigated and it is suggested how those findings might be taken into account in the design of computer assisted translation tools.
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