Mass adoption of neural machine translation (NMT) tools in the translation workflow has exerted a significant impact on the language services industry over the last decade. There are claims that with the advent of NMT, automated translation has reached human parity for translating news (see, e.g. Popel et al. 2020). Moreover, some machine…

We examine the stylistic aspects of L2 translations using a set of quantifiable descriptors. The sample includes 40 translations of a promotional text from Czech into English and French produced by novices and professional translators. The general stylistic competence is slightly higher in the group of professionals, although the overall quality…

The article attempts to determine whether translation errors (in particular semantic and stylistic ones) in translator-training settings are predominantly the result of translation directionality, i.e. of the fact that the student translators are translating into their L2 and that their language competence in L2 is not as strong as in their L1, or…

The purpose of this paper is to present an experimental study on summative assessment in translation teaching. The paper emphasises the need to use, as an alternative to traditional assessment (i.e. the translation of a text under exam conditions), multidimensional assessment based on a range of criterion-referenced and competence-based assessment…

Machine translation is currently undergoing a paradigm shift from statistical to neural network models. Neural machine translation (NMT) is difficult to conceptualise for translation students, especially without context. This article describes a short in-class evaluation exercise to compare statistical and neural MT, including details of student…

In this study, we examined whether interpreters and interpreting trainees are better predisposed to respeaking than people with no interpreting skills. We tested 57 participants (22 interpreters, 23 translators and 12 controls) while respeaking 5-minute videos with two parameters: speech rate (fast/slow) and number of speakers (one/many). Having…