Given the rapid strides in quality made by automated translation since the advent of Neural Machine Translation, questions regarding the need and role of Post-Editing (PE) may need revisiting. This paper discusses this in light of a survey of opinions from two cohorts of post-graduate students of translation. The responses indicate that the role of PE may need further elaboration in terms of aspects such as grammar, lexis and style, with lexis and style being the main sites requiring human intervention. Also, contrary to expectations, responses generally show marked hesitation in considering quasi-texts as final without PE even in case of disposable texts. The discussion here pertains to English-Chinese translation, but may resonate with other language pairs as well.

With increasing acknowledgement of enhanced quality now achievable by Machine Translation, new possibilities have emerged in translation, both vis-à-vis division of labour between human and machine in the translation process and acceptability of lower quality of language in exchange for efficiency. This paper presents surveys of four cohorts of post-graduate students of translation from the University of Macau to see if perceived trainee awareness and preparedness has kept pace with these possibilities. It is found that trainees across the years generally lack confidence in their perceived awareness, are hesitant in employing MT, and show definite reservations when reconsidering issues such as quality and division of labour. While the size of respondents is small, it is interesting to note that the awareness and preparedness mentioned above are found to be similar across the four years. The implication for training is that technology be fully integrated into the translation process in order to provide trainees with a template/framework to handle diverse situations, particularly those that require offering translations of a lower quality with a short turnaround time. The focus here is on Chinese-English translation, but the discussion may find resonance with other language pairs. Keywords Translator training, Computer-Assisted Translation, Machine Translation, translation pedagogy, Chinese-English translation