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Jolita Horbačauskienė

Abstract

Currently various industries using translation services stress the necessity of analytical, critical and practical knowledge of 2 foreign languages, substantial skills of translation technologies, as well as transferable skills for professional translator performance. A changing translator profile causes a shift in translation study programmes towards the development of transferable skills along with translation-related skills. Therefore, the paper focuses on employers’ expectations in relation to the abilities and skills of professionally trained translators. The outcomes of this study reflect the overall situation in the country, still undergoing significant changes in the translation-related industry from the perspective of employers who agree that together with translation-related skills graduates of translation programmes should possess a range of transferable skills, which empower them to act professionally in a changing environment.

Open access

Greta Danilaviciene, Jolita Horbacauskiene and Ramune Kasperaviciene

Abstract

The translation of elements of formulaic language is extremely difficult in subtitles or voice-over due to time and space constraints. Besides, it is very difficult to provide a comprehensive definition of formulaic language as its sequences exist in so many forms. Traditionally, 6 basic formulas are distinguished: polywords, phrasal constraints, meta-messages, sentence builders, situational utterances, and verbatim texts. The analysis of subtitles and a voice-over version of a film shows that differences in the procedures applied for the translation of formulaic language are insignificant, and the strategies used are distributed almost evenly between preservation of content, transformation and localisation.

Open access

Jolita Horbacauskiene and Ramune Kasperaviciene

Abstract

For several decades, there has been a heated debate about the value of providing corrective feedback in writing assignments in English as a foreign language (EFL) classes. Despite the fact that corrective feedback in writing has been analysed from various angles, learners’ expectations regarding feedback given by language instructors are still to be considered, especially in different learning settings. Student attitudes have been found to be associated with motivation, proficiency, learner anxiety, autonomous learning, etc. (Elwood & Bode, 2014). Thus, the aim of this paper was to compare EFL learners’ attitudes towards corrective feedback and self-evaluation of writing skills in different learning settings. Students at two technological universities in France and Lithuania were surveyed and asked to complete an anonymous questionnaire combining the Likert scale and rank order questions. The results indicate that frequency of writing assignments seems to have little or no impact on students’ self-evaluation of writing skills. Moreover, although the two groups of students showed preference for feedback on different error types (e.g., feedback on structure vs. feedback on grammar), nevertheless, indirect corrective feedback with a clue was favoured by all the respondents.

Open access

Issues in Machine Translation

A case of mobile apps in the Lithuanian and English language pair

Gilvilė Stankevičiūtė, Ramunė Kasperavičienė and Jolita Horbačauskienė

Abstract

Machine translation (MT) is still a huge challenge for both IT developers and users. From the beginning of machine translation, problems at the syntactic and semantic levels have been faced. Today despite progress in the development of MT, its systems still fail to recognise which synonym, collocation or word meaning should be used. Although mobile apps are very popular among users, errors in their translation output create misunderstandings. The paper deals with the analysis of machine translation of general everyday language in Lithuanian to English and English to Lithuanian language pairs. The results of the analysis show that more than two thirds of all the sentences were translated incorrectly, which means that there is a relatively small possibility that a mobile app will translate sentences correctly. The results are disappointing, because even after almost 70 years of MT research and improvement, researchers still cannot offer a system that would be able to translate with at least 50% correctness.