Postediting machine translation output and its revision: subject-matter experts versus professional translators

The present research compares engineers’ and professional translators’ postediting a technical text in terms of speed, documentation and changes. It also compares the postedited texts with regard to quality. Further, we explore which of the following workflows is faster and produces outputs of highe...

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Detalhes bibliográficos
Autor: Temizöz, Özlem
Tipo de documento: tese
Estado:Versão publicada
Data de publicação:2013
País:España
Recursos:Universitat Rovira i virgili (URV)
Repositório:Repositori Institucional de la Universitat Rovira i Virgili
OAI Identifier:oai:urv.cat:TDX:1287
Acesso em linha:https://hdl.handle.net/20.500.11797/TDX1287
http://hdl.handle.net/10803/128204
Access Level:Acceso aberto
Palavra-chave:8 - Lingüística i literatura
378 - Ensenyament superior. Universitats
371 - Organització i gestió de l'educació i de l'ensenyament
Descrição
Resumo:The present research compares engineers’ and professional translators’ postediting a technical text in terms of speed, documentation and changes. It also compares the postedited texts with regard to quality. Further, we explore which of the following workflows is faster and produces outputs of higher quality: Postediting MT output by engineers and revising the postedited text by professional translators, or vice-versa. The findings suggest that expertise and experience in the subject-matter are the main factors determining postediting quality. When the recurrent errors are penalized, the engineers’ postediting of technical texts is of significantly higher quality than the translators’. The translators’ and the engineers’ postediting and revision speed did not differ significantly. For technical texts, the quality improvement brought about by engineer-revision of translator-postediting is higher than vice-versa. Further, the quality of the postedited texts and their revised versions (either performed by professional translators or engineers) changes significantly as a result of penalizing and unpenalizing recurrent errors.