Post-editing Machine Translation in MateCat: a classroom experiment

Autor:	Katrin Herget
Jazyk:	angličtina
Rok vydání:	2021
Předmět:	MateCat Machine translation Higher education Translation technology classes business.industry Teaching Educational systems Higher Education computer.software_genre Mathematics education Learning Post-editing Psychology business computer
Zdroj:	RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia instname
Popis:	[EN] Advances in machine translation resulted in an increase of both volume and quality of machine-translated texts. However, machine translation still requires humans to post-edit the translation. This paper proposes a product-based approach of a post-editing (PE) experiment that was carried out with a total of 10 MA translation students. The goal of this study comprised both the analysis of the post-editing results performed by student translators involving a machine-translated text in MateCat and the subsequent error markup. By comparing the quality reports obtained at the end of the post-editing process, we analysed the linguistic quality results and observed a heterogeneous error distribution, considerable divergence in severity level ratings and a huge span of TTE (time to edit). This study aims at making a contribution to the integration of post-editing activities into the translation technology classroom for students without prior experience in PE. The author would like to thank the MA students who participated in this experiment for their time and feedback.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::18870df4c3a46274386b3b15915ec9c4 http://hdl.handle.net/10251/172666 Zobrazit plný text záznamu