This article presents the results of an experiment with eleven students from two universities that translated and post-edited threeliterarytextsdistributed on the first and last days of their... Show moreThis article presents the results of an experiment with eleven students from two universities that translated and post-edited threeliterarytextsdistributed on the first and last days of their translation technology modules. The source texts were marked with units of creative potential to assess creativity in the target texts (before and after training). The texts were subsequently reviewed by an independentprofessional literary translator and translation trainer. The results show that there is no quantitative evidence to conclude that the training significantly affects students’ creativity. However, after the training, a change is observed both in the quantitative data and in the reflective essays, i.e. the students are more willing to try creative shifts and they feel more confident to tackle machine translation (MT)issues, while also showing a higher number of errors. Further, we observe that students havea higher degree of creativity in human translation (HT), but significantly fewer errors in post-editing (PE)overall, especially at the start of the training, than in HT. Show less
In het Nederlands wordt vaak over dementie gesproken met krachtige beeldspraken als “opgaan in de mist”, of “in je hersenen verdwalen”. Maar de meeste metaforen zijn sterk cultureel bepaald. Hoe... Show moreIn het Nederlands wordt vaak over dementie gesproken met krachtige beeldspraken als “opgaan in de mist”, of “in je hersenen verdwalen”. Maar de meeste metaforen zijn sterk cultureel bepaald. Hoe denken en praten mensen met een migratieachtergrond over dementie en welke metaforen gebruiken zij daarbij? Show less
This paper explores how students conceptualise the processes involved in human translation (HT) and machine translation (MT), and how they describe the similarities and differences between them.... Show moreThis paper explores how students conceptualise the processes involved in human translation (HT) and machine translation (MT), and how they describe the similarities and differences between them. The paperpresents the results of a survey involving university students (B.A. and M.A.) taking a course on translation who filled out an online questionnaire distributed in Finnish, Dutch and English. Our study finds that students often describe both HT and MT in similar terms, suggesting they do not sufficiently distinguish between them and do not fully understand how MT works. The current study suggests that training in Machine Translation Literacy may need to focus more on the conceptualisations involved and how conceptual and vernacular misconceptions may affect how translators understand human and machine translation. Show less
AbstractIntroductionPeople with dementia from migrant and ethnic minority (MEM) groups often receive suboptimal care. Differences in perceptions, values and preferences, and linguistic barriers may... Show moreAbstractIntroductionPeople with dementia from migrant and ethnic minority (MEM) groups often receive suboptimal care. Differences in perceptions, values and preferences, and linguistic barriers may complicate communication between persons with dementia, their families and healthcare professionals. Metaphor analysis can provide unique insight into the lifeworld of people with dementia and their informal caregivers. This study identified the metaphors with which informal caregivers of persons with dementia from diverse cultural-linguistic backgrounds understand and discuss dementia.MethodsWe conducted 7 focus groups (n = 42) and 12 interviews (n = 13) with informal caregivers of persons with dementia living in the Netherlands from six different cultural backgrounds: Dutch, Chinese, Turkish, Moroccan, Surinamese, and Dutch-Antillean. Interviews, in the native tongue of participants, were analyzed for the presence of direct and indirect metaphor.ResultsThe results indicate a conspicuous lack of metaphor to reflect on the nature and experience of having dementia. Two typical conceptual metaphors in health communication (journey/war) are virtually absent in all MEM groups. Furthermore, results suggest a one-sided and negative outlook on dementia, with an emphasis on persons with dementia as ‘childlike’ or ‘crazy’.ConclusionOur results suggest a lack of extensively available sophisticated (metaphorical) language to consider daily life with persons with dementia. There is a clear need to address the stigma and lack of medical knowledge surrounding dementia in these MEM groups and to carry out more cross-linguistic and cross-cultural research to explore which metaphors aid understanding and lead to the empowerment and restoration of self-worth of people with dementia. Show less
This article reflects on the current training in machine translation and post-editing that students enrolled in the Master Translation at Leiden University Centre for Linguistics are receiving by... Show moreThis article reflects on the current training in machine translation and post-editing that students enrolled in the Master Translation at Leiden University Centre for Linguistics are receiving by discussing the findings of three recent studies. Especially at the master’s level, machine translation and post-editing are becoming increasingly important in translator training curricula with an eye to changing workflows in the language industry. Yet one question that remains is which specific skills, competences and knowledge future translators need, and to what degree an understanding of the computational side of machine translation is required. Show less
Machine Translation (MT), the process by which a computer engine such as Google Translate or Bing automatically translates a text from one language into another without any human involvement, is... Show moreMachine Translation (MT), the process by which a computer engine such as Google Translate or Bing automatically translates a text from one language into another without any human involvement, is increasingly used in professional, institutional and everyday contexts for a wide range of purposes.While a growing number of studies has looked at professional translators and translation students, there is currently a lack of research on nontranslator users and uses in multilingual contexts.This paper presents a survey examining how, when and why students at Leiden University’s Faculty of Humanities use MT. A questionnaire was used to determine which MT engines students use and for what purposes, and gauge their awareness of issues concerning privacy, academic integrity and plagiarism. The findings reveal a widespread adoption of Google Translate and indicate that students use MT predominantly to look up single words, as an alternative to a dictionary. Many seemed sceptical about thevalue of MT for educational purposes, and many assumed that the use of MT is not permitted by lecturers for graded assignments, especially in courses focusing on language skills.The results demonstrate a clear need for more MT literacy. Students may not need practical training in how to use MT, but there is much room for improvement in terms of when and why they use it. Show less
This article presents a quantitative cross-register comparison of the forms and frequency of linguistic metaphor in fiction based on a 45,000-word annotated corpus containing excerpts from 12... Show moreThis article presents a quantitative cross-register comparison of the forms and frequency of linguistic metaphor in fiction based on a 45,000-word annotated corpus containing excerpts from 12 contemporary British-English novels sampled from the British National Corpus. The results for fiction are compared to those for three other registers, namely news texts, academic discourse and conversations. The linguistic manifestations of metaphor in the corpus were identified using the MIPVU procedure (Steen et al., 2010), a revised and extended version of the original Metaphor Identification Procedure, or MIP, as developed by the Pragglejaz Group (2007). Contrary to common expectations, fiction was not the register with the highest number of metaphors, but was situated in between academic discourse and news on the one hand, and conversation on the other. However, it turned out that metaphor signals and direct expressions of metaphor (e.g. simile) were typical of fiction, as has been claimed in the literature (e.g. Goatly, 1997; Lodge, 1977; Sayce, 1953). Based on these quantitative findings, this article will show that fiction does not contain more metaphors than the other registers, but rather, different ones. Show less
