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  Interactive translation prediction versus conventional post-editing in practice: a study with the CasMaCat workbench

Sanchis-Trilles, G., Alabau, V., Buck, C., Carl, M., Casacuberta, F., García Martínez, M., et al. (2014). Interactive translation prediction versus conventional post-editing in practice: a study with the CasMaCat workbench. Machine Translation, 28(3-4), 217-235. doi:10.1007/s10590-014-9157-9.

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Sanchis-Trilles2014_Article_InteractiveTranslationPredicti.pdf (Publisher version), 575KB
 
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 Creators:
Sanchis-Trilles, Germán, Author
Alabau, Vicent, Author
Buck, Christian, Author
Carl, Michael, Author
Casacuberta, Francisco, Author
García Martínez, Mercedes, Author
Germann, Ulrich, Author
González Rubio, Jesús, Author
Hill, Robin L. , Author
Koehn, Philipp, Author
Leiva, Luis A., Author
Mesa-Lao, Bartholomé, Author
Ortiz Martínez, Daniel, Author
Saint-Amand, Herve, Author
Tsoukala, Chara1, Author           
Vidal, Enrique, Author
Affiliations:
1External Organizations, ou_persistent22              

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Free keywords: CAT; SMT; Interactive translation prediction; Post-editing; Field trial; User studies
 Abstract: We conducted a field trial in computer-assisted professional translation to compare interactive translation prediction (ITP) against conventional post-editing (PE) of machine translation (MT) output. In contrast to the conventional PE set-up, where an MT system first produces a static translation hypothesis that is then edited by a professional (hence “post-editing”), ITP constantly updates the translation hypothesis in real time in response to user edits. Our study involved nine professional translators and four reviewers working with the web-based CasMaCat workbench. Various new interactive features aiming to assist the post-editor/translator were also tested in this trial. Our results show that even with little training, ITP can be as productive as conventional PE in terms of the total time required to produce the final translation. Moreover, translation editors working with ITP require fewer key strokes to arrive at the final version of their translation.

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Language(s): eng - English
 Dates: 2014-01-242014-09-042014-11-21
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1007/s10590-014-9157-9
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Title: Machine Translation
Source Genre: Journal
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Publ. Info: Dordrecht, The Netherlands : Springer Science+Business Media
Pages: - Volume / Issue: 28 (3-4) Sequence Number: - Start / End Page: 217 - 235 Identifier: ISSN: 0922-6567