The relevance of translation and law degrees as pathways to professional legal translation is the subject of persistent debate, but there is limited research on the relationship between legal translators' backgrounds and competence levels in practice. This study compares the revision performance of several groups of institutional translators (44…

In the past couple of decades, machine translation (MT), whether phrase-based statistical or neural MT, has made considerable progress and has become increasingly common in specialised translation workflows. More studies on MT in legal contexts have been conducted in the past several years, and MT has been and continues to be used in international…

This study combines product- and process-oriented research methods and tools to observe whether and how the presence of pre-translated text affects translation quality and influences the translator's research patterns. It is part of the LeMaTTT project, a simulated longitudinal empirical study exploring the impact of MT on info-mining and thematic…

Legal translators are routinely faced with defective source texts in their professional practice while being expected to produce effective translations despite such quality issues. Given the high-quality expectations required in legal translation, we have brought this professional reality into the classroom by outlining a quality control activity…

In recent years, machine translation post-editing (MTPE or PE for short) has been steadily gaining ground in the language industry. However, studies that examine translators' perceptions of, and attitudes towards, MTPE paint a somewhat negative picture, with PE pricing methods and rates being a major source of dissatisfaction. While the European…

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…

Motivated by the urgent need to investigate the possibilities for re-positioning the human translator and his/her educator in the machine translation (MT) age, this article explores the dynamics of the human-machine dance in the translation classroom. The article discusses the results of a collaborative learning experiment which was conducted in…

The study focuses on literary translation between languages of low diffusion (LLD) from the perspective of a culture using such a language. The position of a language group in the world translation system determines the general flow of literary translation, but the specifics for the translation of an individual LLD may depend on a number of…

Drawing from research on revision competence and revision didactics, and based on the proposal of a multi-component revision competence model, a short-term revision course was offered in 2015 as part of a Specialized Translation module. During the course, students were also involved in an experimental study whose overall aim was to investigate the…

It has been argued that the growing impact of new technologies on society should be reflected in education in response to the digital generation's extensive dependence on digital tools. This paper focuses on the incorporation of digital technologies into translator training by comparing the benefits and drawbacks of "wikis," a…

This paper presents the ERASMUS+ "DigiLing" project, which aims to teach and improve linguists' and translators' skills and knowledge of digitalisation to prepare them for today's job market. Against this background, it discusses the development of digital competencies and distinguishes them from traditional domain-specific and general…

Increasing project complexity and a high level of specialization in the language industry have resulted in a demand for translation professionals with sophisticated technical skills. This has made computer-assisted translation (CAT) tools indispensable for translators in order to meet project requirements. With a rapidly changing industry…

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…