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Localisation Focus

The International Journal of Localisation

Localisation Focus–The International Journal of Localisation provides a forum for localisation professionals and researchers to discuss and present their localisation-related work, covering all aspects of this multi-disciplinary field, including software engineering and HCI, tools and technology development, cultural aspects, translation studies, human language technologies (including machine and machine assisted translation), project management, workflow and process automation, education and training, and details of new developments in the localisation industry. Proposed contributions are peer-reviewed thereby ensuring a high standard of published material. Localisation Focus–The International Journal of Localisation is distributed worldwide to libraries and localisation professionals, including engineers, managers, trainers, linguists, researchers and students. Indexed on a number of databases, this journal affords contributors increased recognition for their work. Localisation-related articles, book reviews, perspectives, insights and correspondence are all welcome.

Productivity and Quality in the Post-editing of Outputs from Translation Memories and Machine Translation

Volume 7 Issue 1


Author: Ana Guerberof Arenas


Machine-translated segments are increasingly included as fuzzy matches within the translation-memory systems in the localisation workflow. This study presents preliminary results on the correlation between these two types of segments in terms of productivity and final quality. In order to test these variables, we set up an experiment with a group of eight professional translators using an on-line post-editing tool and a statistical-based machine translation engine. The translators were asked to translate new, machine-translated and translation-memory segments from the 80-90 percent value range using a post-editing tool without actually knowing the origin of each segment, and to complete a questionnaire. The findings suggest that translators have higher productivity and quality when using machine-translated output than when processing fuzzy matches from translation memories. Furthermore, translators' technical experience seems to have an impact on productivity but not on quality.

Keywords: Translation memory, machine translation, post-editing, revision, productivity, quality, errors, editing, professional translators, experience, fuzzy match, processing speed, localisation

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