Crowdsourcing Translation as MT Post-editing of Health-related Information: An Experience of Cloud-based Smartphone App
نویسندگان :
Akbar Hesabi ( University of Isfahan ) , Marziyeh Khalilizadeh Ganjalikhani ( University of Isfahan )
چکیده
This project concerns with crowdsourcing Translation as a post-editing means of translations produced via Machine Translation, through a cloud-based Smartphone App (Telegram) as a crowdsourcing platform. The selected Translation Machines were Google Translate website and Farazin Translator website. As a first step, random expressions from health-related texts/sources were collected as the required data, and then they were given to Google Translate and Farazin Translator to be translated. In the third step a Telegram Bot was designed to share the MT outcome with Medical students as well as senior Translation students to grade, to edit or to correct in case of errors. The final step not only consisted of a quality assessment between the two translation outcomes providing a statistical analysis but also included a comparison between translations done by medical and translation student, as two closed crowdsourcer groups, to detect which group had a better performance. کليدواژه ها
Cloud-Based App, Crowdsourcing, Machine Translation, Post-editing, Telegram Platformکد مقاله / لینک ثابت به این مقاله
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