Post-editing

O’Brien, Sharon

doi:10.1075/hts.5.pos3

Handbook of Translation Studies

2021

DOI: 10.1075/hts.5.pos3

|View full text |Cite

Post-editing

Sharon O’Brien

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2022

2024

Publication Types

Select...

Article2

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Mind the gap

Pérez

2022

Babel

View full text Add to dashboard Cite

Has post-editing changed the nature of translation? Are these tasks two sides of the same coin? These are some of the questions that recent developments in machine translation have brought to translation studies. The quality of the texts rendered by the new neural engines is good enough to challenge the traditional role of the human translator. Some voices even question whether there might be any place left for translators if, in the near future, their role is finally superseded by that of the post-editor. This paper offers a comprehensive view of the many aspects of post-editing with a view to shedding some light on the nature of this task. I first explore how the progress in machine translation has turned post-editing into an essential activity. Then, I present a proposal for a categorization of research areas in post-editing within the framework of translation studies. The central discussion of this paper revolves around three key ideas: (1) the conceptualization of post-editing as more than a simple, fast and inexpensive task; (2) the framing of post-editing as a dynamic process; and (3) the claim that defining quality in machine translation post-editing is not as straightforward as it may seem. The ultimate goal of this paper is to lay the foundations for further discussion into what it is that post-editing means for translation studies.

show abstract

Mind the gap

Pérez

2022

Babel

View full text Add to dashboard Cite

show abstract

MT error detection and correction by Chinese language learners

Zhang,

Osborne,

Moorkens

2024

TIS

View full text Add to dashboard Cite

This article analyzes texts that have been generated by machine translation (MT) and post-edited by native English-speaking trainee translators (English>Chinese) who are also Chinese language learners enrolled in a four-year undergraduate translation program. The project examines the work product of trainee translators to categorize 122 errors that are (un)noticed and (un)corrected by them. MT errors in the Accuracy category were best identified and corrected, followed by those in the Lexicon and Fluency categories. Trainee translators who were advanced language learners outperformed the intermediate group in MT error detection and correction, especially in the Lexicon category. This study sheds light upon the use of raw MT output as meaningful input for trainee translators who are in the process of learning Chinese. Its findings provide information regarding the type of exercises needed in language learning and translation training for students with different levels of language proficiency.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Post-editing

Cited by 2 publications

References 6 publications

Mind the gap

Mind the gap

MT error detection and correction by Chinese language learners

Contact Info

Product

Resources

About