L10N Journal

Introduction

2024-03-05T10:27:45+01:00

Introduction to the conference issue Translation, Interpreting & Culture 2023: Virality and Isolation in the Era of Deepening Divides.

Translation and post-editing performance of translation students – a cross-sectional analysis

2023-10-29T10:27:00+01:00

This study presents partial results of a comprehensive study to reveal what role PACTE’s translation sub-competences play in human translation and in the post-editing of machine translated texts. In the PACTE model, both language competence and background knowledge related to the source text are given a prominent role. The present research explores how these factors are associated with MA students' translation performance. 20 first-year and 27 second-year master’s students of translation (University of Szeged, Hungary) translated or post-edited the abstract of a study on bilingualism from English to Hungarian and completed a test measuring their relevant thematic knowledge and language tests assessing their source language competence. Our analysis focuses on comparing the quality of translated and post-edited texts, and on the time needed to complete the target text. The correlations between test scores, on the one hand, and error types and error numbers in the translated and post-edited Hungarian target language texts, on the other hand, are also examined. Our results indicate that both at the beginning and at the end of the training, post-editing was faster than human translation and post-edited texts contained fewer errors than human translations. In the second-year sample, thematic knowledge and time on task showed significant correlations with performance indices.

Portuguese translators' attitude to MT and its impact on their profession

2023-11-07T14:03:51+01:00

Advances in Neural Machine Translation in recent years have brought these systems closer to delivering on the promise of universal, instant translatability. Magnified by the release of successive iterations of generative AI systems, recent news heralds both a new era for translation and the obsolescence of the translator. Drawing on data from recent language industry surveys produced by national and international organizations, as well as a specific survey on the Portuguese market with a longitudinal dimension, this paper seeks to determine the impact of technology, particularly MT, on the perceptions of translators and their career choices. The findings indicate that MT is widely used in the industry, but only a third of MT users rate their experience as positive. MT projects most frequently involve human participation as post-editors. MT is seen as having improved despite several shortcomings. However, greater incorporation of technology is seen as considerably reducing satisfaction and potentially triggering significant attrition. Knowledge of MT and first-hand experience are seen as positively influencing attitudes towards MT.

Translation Project Management: Duties, Competences and Training. What is the scenario like in Spain?

2023-09-15T19:41:41+02:00

With the introduction of new technologies and the rise of globalization, the translation industry has undergone significant transformation since the end of the 20th century. What was originally considered an individual and self-employed activity has evolved to meet the demands of the language services industry over the last two decades, resulting in a virtual working environment. It is within this evolving landscape that the role of the Translation Project Manager (PM) has emerged, offering an interesting alternative to students aspiring to diverge from the more traditional career paths linked to Translation and Interpreting (T&I). Based on an observational study of Spanish university curricula, this study aims to discuss the training that future PMs are receiving in regard to Translation Project Management (TPM), focusing on the training content (or lack thereof). The primary objective is to determine whether university training aligns with the demands of the labor market and whether future PMs are adequately prepared for their professional journey.

Integration of Machine Translation Tools in Software Localization: mission (im)possible?

2024-03-05T10:20:50+01:00

The use of machine translation tools in various translation related activities has exponentially increased, not only because of the pandemic and post-pandemic context, the growth of the language industry, but also because of the current technological development of machine translation tools. Researchers, translators and developers actively discuss machine translation capabilities, its impact on translation and language, and challenges it brings. However, when it comes to software localization, possibilities of machine translation tools seem overestimated and limited, not only because of the quality of the output the machine translation tools produce, but also because of technical capacities to recognize programming language and handle difficult scenarios. This article aims to introduce possibilities and limitations of integrating machine translation tools in the process of software localization into the Lithuanian language. Here the term “integration” is used as the application of machine translation tools in the workflow of localization so as to speed up the process and help translators, but not as the technological integration when machine translation tools are integrated with computer aided translation (CAT) tools. The article presents an experiment during which several machine translation tools, such as Google Translate, DeepL, Vilnius University machine translation tool and Tildė machine translation tool, were tested with the Lithuanian language as the low-resourced language. The four machine translation tools were selected due to their popularity and current development in and for the Lithuanian language (Utka et al. 2020). The machine translation tools were given to translate .rc2 or .txt software-related resource files. The output quality produced in the Lithuanian language was compared in terms of text cohesion, term accuracy, identification of segments to be localized and damaged programming code. Moreover, the machine translation outputs were compared with the output of professional translation and localization CAT tools such as Passolo and Trados. The results showed that none of the machine translation tools used, despite the current integration of artificial intelligence solution, can produce high-quality translated text in the Lithuanian language due to the assumption that the Lithuanian language (with around 3 million speakers) is not commercially attractive. The output produced cannot be applied to speed up or ease localization in terms of the output text quality.

Moniz, Helena, and Parra Escartín, Carla (eds). 2023. Towards Responsible Machine Translation: Ethical and Legal Considerations in Machine Translation. Springer Cham.

2024-03-05T10:32:31+01:00

Review of: Moniz, Helena, and Parra Escartín, Carla (eds). 2023. Towards Responsible Machine Translation: Ethical and Legal Considerations in Machine Translation. Springer Cham.

Final Variable

2024-03-05T10:37:50+01:00

The Final Variable section introduces the following publications:

The Special Issue on Translation Automation and Sustainability in The Journal of Specialised Translation;

De-mystifying Translation;

The Translation of Realia and Irrealia in Game Localization;

50 let videoher.