Machine-Assisted Literary Translation, 2019-2021

This project aimed to improve products and processes related to translators' interaction with technology, examine the efficacy of various working methods, and assess new training approaches for the translation workplace. With a focus on empowering translators to use machine translation effectively and boost job satisfaction, the project sought to raise professional standards and contribute to the multilingual economy. The deposit contains data for two studies where English-to-Chinese translators used neural machine translation (MT) to translate science fiction short stories in Trados Studio. One of the studies (t-p) compares post-editing to a ‘no MT’ condition. The other (segmentation) examines two ways of presenting the texts on screen for post-editing, namely by segmenting them into paragraphs or into sentences. The dataset is licenced under a Creative Commons "CC BY-NC-SA 2.5" license.