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Improving the post-editing experience using translation recommendation: a user study

He, Yifan, Ma, Yanjun, Roturier, Johann, Way, Andy ORCID: 0000-0001-5736-5930 and van Genabith, Josef ORCID: 0000-0003-1322-7944 (2010) Improving the post-editing experience using translation recommendation: a user study. In: AMTA 2010 - 9th Conference of the Association for Machine Translation in the Americas, 31 October - 4 November 2010, Denver, CO, USA.

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Abstract

We report findings from a user study with professional post-editors using a translation recommendation framework (He et al., 2010) to integrate Statistical Machine Translation (SMT) output with Translation Memory (TM) systems. The framework recommends SMT outputs to a TM user when it predicts that SMT outputs are more suitable for post-editing than the hits provided by the TM. We analyze the effectiveness of the model as well as the reaction of potential users. Based on the performance statistics and the users’comments, we find that translation recommendation can reduce the workload of professional post-editors and improve the acceptance of MT in the localization industry.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Subjects:Computer Science > Machine translating
DCU Faculties and Centres:Research Initiatives and Centres > Centre for Next Generation Localisation (CNGL)
Publisher:Association for Machine Translation in the Americas
Official URL:http://amta2010.amtaweb.org/AMTA/html/toc.htm
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland
ID Code:15803
Deposited On:06 Dec 2010 14:12 by Shane Harper . Last Modified 09 Nov 2018 15:59

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