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The first Automatic Translation Memory Cleaning Shared Task

dc.contributor.authorBarbu, Eduard
dc.contributor.authorParra Escartín, Carla
dc.contributor.authorBentivogli, Luisa
dc.contributor.authorNegri, Matteo
dc.contributor.authorTurchi, Marco
dc.contributor.authorOrasan, Constantin
dc.contributor.authorFederico, Marcello
dc.date.accessioned2017-01-25T14:59:43Z
dc.date.available2017-01-25T14:59:43Z
dc.date.issued2017-01-21
dc.identifier.citationBarbu, E., Escartín, C.P., Bentivogli, L., Negri, M., Turchi, M., Orasan, C., & Federico, M. (2016). The first Automatic Translation Memory Cleaning Shared Task. Machine Translation, 30 (3-4), pp 145-166.
dc.identifier.issn0922-6567
dc.identifier.doi10.1007/s10590-016-9183-x
dc.identifier.urihttp://hdl.handle.net/2436/620353
dc.descriptionThis is an accepted manuscript of an article published by Springer in Machine Translation on 21/01/2017, available online: https://doi.org/10.1007/s10590-016-9183-x The accepted version of the publication may differ from the final published version.
dc.description.abstractThis paper reports on the organization and results of the rst Automatic Translation Memory Cleaning Shared Task. This shared task is aimed at nding automatic ways of cleaning translation memories (TMs) that have not been properly curated and thus include incorrect translations. As a follow up of the shared task, we also conducted two surveys, one targeting the teams participating in the shared task, and the other one targeting professional translators. While the researchers-oriented survey aimed at gathering information about the opinion of participants on the shared task, the translators-oriented survey aimed to better understand what constitutes a good TM unit and inform decisions that will be taken in future editions of the task. In this paper, we report on the process of data preparation and the evaluation of the automatic systems submitted, as well as on the results of the collected surveys.
dc.formatapplication/pdf
dc.language.isoen
dc.publisherSpringer
dc.relation.urlhttp://link.springer.com/10.1007/s10590-016-9183-x
dc.subjectTranslation memories
dc.subjectTranslation memory cleaning
dc.subjectNatural language processing
dc.subjectMachine learning
dc.titleThe first Automatic Translation Memory Cleaning Shared Task
dc.typeJournal article
dc.identifier.journalMachine Translation
dc.date.accepted2016-12-19
rioxxterms.funderUniversity of Wolverhampton
rioxxterms.identifier.projectUoW250117CO
rioxxterms.versionAM
rioxxterms.licenseref.urihttps://creativecommons.org/CC BY-NC-ND 4.0
rioxxterms.licenseref.startdate2018-01-20
dc.source.volume30
dc.source.issue3-4
dc.source.beginpage145
dc.source.endpage166
refterms.dateFCD2018-10-19T08:43:46Z
refterms.versionFCDAM
refterms.dateFOA2018-01-20T00:00:00Z
html.description.abstractThis paper reports on the organization and results of the rst Automatic Translation Memory Cleaning Shared Task. This shared task is aimed at nding automatic ways of cleaning translation memories (TMs) that have not been properly curated and thus include incorrect translations. As a follow up of the shared task, we also conducted two surveys, one targeting the teams participating in the shared task, and the other one targeting professional translators. While the researchers-oriented survey aimed at gathering information about the opinion of participants on the shared task, the translators-oriented survey aimed to better understand what constitutes a good TM unit and inform decisions that will be taken in future editions of the task. In this paper, we report on the process of data preparation and the evaluation of the automatic systems submitted, as well as on the results of the collected surveys.


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