Can translated language really be analysed based on published texts, given the many agents that may influence the translator's work before publication? This article seeks to address this question through a parallel corpus study of English business articles, their German translation manuscripts and the published German translations. The objects of study are passive voice constructions. I analyse the frequency of instances where translators used the active voice to translate verbs that are in passive voice in the source text (and vice versa), and whether editors maintained that construction or intervened to change it again. The study finds that translators use the passive voice extensively to translate active voice constructions. Editors intervene often to change such constructions back to active voice. This suggests that translators mainly passivise while editors mainly activise constructions. The tense used in the source text is shown to have an effect on whether these interventions take place or not. The article argues that there is a difference between what translated language actually is and what we find in published texts.
Due to the advancement and application of machine translation (MT) technology, MT post-editing (PE) has now been provided as an independent service in today’s translation market with its own
The study reported in the paper investigates the structure of L2 self-corrections in the speech of 30 Hungarian learners of English and 10 Hungarian native speakers. The aim of the research is to examine what the well-formedness of the corrections, the use of editing terms, the placement of cut-off points and the effect of the participants' level of proficiency on the structure of self-repairs reveal about the psycholinguistic processes of speech production. The results of the study lend additional support for modular models of speech production (e.g., Levelt 1983, 1989; Levelt et al. 1999) and reveal an important role of pragmatic constraints in psycholinguistic processing.
edited volume by Milton and Bandia 2009; Van Es and Heilbron 2015 ). On the other hand, and on a smaller scale, however, important relations take place also between the agents involved in the production (and publication) of individual translations
Post-editing of machine translation is gaining popularity as a solution to the ever-increasing demands placed on human translators. There has been a great deal of research in this area aimed at determining the feasibility of post-editing and at predicting post-editing effort based on source-text features and machine translation errors. However, considerably less is known about the mental workings of post-editing and post-editors’ decision-making or, in particular, the relationship between post-editing effort and different mental processes. This paper investigates these issues by analysing data from a think-aloud study through the lens of eye movements and subjective ratings obtained in a separate task. The results show that mental processes associated with grammar and lexis are significantly associated with cognitive effort in post-editing. This association was not observed for other aspects of the task concerning, for example, discourse or the real-world use of the text. In addition, it was noted that lexical issues are linked to long sequences of thought processes. The paper shows that lexis plays a central role in post-editing, and argues that more emphasis should be placed on this issue in future research and in post-editor training.
In translation process
and language production research, pauses are seen as indicators of cognitive
processing. Investigating the correlations between source text machine
translatability and post-editing effort involves an assessment of cognitive
effort. Therefore, an analysis of pauses is essential. This paper presents data
from a research project which includes an analysis of pauses in post-editing,
triangulated with the Choice Network Analysis method and Translog. Results
suggest that the pause-to-keyboarding ratio does not differ significantly for
sentences deemed to be more suitable for machine translation than for those
deemed to be less suitable. Also, results confirm the finding in research
elsewhere that pause duration and frequency is subject to individual
differences. Finally, we suggest that while pauses provide some indication of
cognitive processing, supplementary methods are required to give a fuller
planned to reach 100 by the time Toni would celebrate his 100th birthday, thus in 2020 two fascicles were edited, one of them has been published ( Farkas 2020 ) and this current one is going to be published in 2021. Keeping the original idea – distributing
This article presents eighteen glosses and emendations borrowed from Turkic dialects into the Slavonic-Russian Pentateuch edited according to the Hebrew Masoretic Text (in manuscripts from the 15th–16th centuries). The first group of these words — including proper names — has Arabic or Persian origins; they came into East Slavonic with obvious Turkic mediation (Skandryja ‘Alexandria’, Bagadad ‘Baghdad’, Misurʹ ‘Egypt’, Šam ‘Damascus’, Isup ‘Joseph’, sturlabʹ ‘astrolabe’, soltan ‘sultan’, olmas ‘diamond’, ambar ‘ambergris’, and brynec ‘rice’). The second group is proper Turkic: saigak ‘saiga antelope’, ošak ‘donkey’, katyrʹ ‘mule’, kirpič ‘brick’, talmač ‘interpreter’, čalma ‘turban’, and saranča ‘locust’. The author agrees with the hypothesis that this glossing/emendation was made for the East Slavonic Judaizers. Furthermore, the author suggests that there was participation of a group of merchants interested in a new and mysterious knowledge promulgated by learned rabbis.