Multivaried acceptance of post-editing in China

Author:

Zheng Jianwei1,Fan Wenjun2

Affiliation:

1. Fuzhou University

2. Wuhan Institute of Technology

Abstract

Abstract Neural machine translation (NMT), proven to be productively and qualitatively competitive, creates great challenges and opportunities for stakeholders in both the market and the education contexts. This paper explores how English-Chinese NMT post-editing (PE) is accepted in China from the perspectives of attitude, practice, and training, based on an integrative digital survey with role-specific popup questions for translators and clients in the market setting, and for translation teachers and students in the education setting. Descriptive statistics and correlation analyses of the survey data suggest Chinese stakeholders’ generally moderate view of PE, with outsiders like clients being more optimistic about PE than are insiders like translators. In the market setting, most translators use PE to different degrees in translating primarily informative texts; here, affiliated translators report a more frequent usage, and employ more sophisticated tools than do part-time or freelance translators. Whereas translators, on the whole, fail to notify clients of their own PE usage, or to charge clients for PE and human translation (HT) differently, most clients express their willingness to accept high-quality PE output for the sake of saving cost and time. In the education setting, despite students’ concealed usage of PE to do HT assignments to varying degrees, and their wish to learn PE out of concern for their future career, PE is generally not taught in translation classrooms of Chinese universities in the form of teaching PE as a course or integrating PE content into traditional translation course.

Publisher

John Benjamins Publishing Company

Subject

Linguistics and Language,Language and Linguistics

Reference32 articles.

1. Machine translation and post-editing: Impact of training and directionality on quality and productivity;Báez;Revista Tradumàtica,2018

2. Post-Editing Human Translations and Revising Machine Translations

3. Identifying the Machine Translation Error Types with the Greatest Impact on Post-editing Effort

4. Shared resources, shared values? Ethical implications of sharing translation resources;Drugan,2010

5. To train post-editors in the background of the global language services industry;Feng;Foreign Language World,2015

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