This monograph offers a comprehensive analysis of machine translation (MT) acceptance, awareness, and quality within Lithuanian society. It moves beyond the predominantly professional-centric perspectives found in existing research to explore the multifaceted experiences of a wide range of users, encompassing students, professionals, and the general public. The study utilizes a mixed-methods approach, combining quantitative survey data with qualitative insights gathered through interviews and eye-tracking experiments. This methodology allows for a nuanced understanding of how various social groups perceive, use, and evaluate MT technologies, considering factors such as usability, satisfaction, and the recognition of potential risks. The research investigates the acceptability of machine-translated output, exploring the degree to which users find it satisfactory and appropriate for their needs. It also examines public awareness of MT capabilities and limitations, focusing on the level of understanding among different user groups regarding the technology’s strengths and weaknesses. A significant aspect of the study is the assessment of machine translation quality, considering both the linguistic accuracy and the overall effectiveness of the output. The findings shed light on the interplay between user expectations, technological capabilities, and societal contexts in shaping the use and acceptance of MT. The monograph is organized into six chapters, beginning with an overview of theoretical and methodological frameworks. Subsequent chapters delve into empirical findings, revealing detailed analyses of user experiences, opinions, and behaviors. Key themes explored include the impact of age, education level, and professional background on MT use and perceptions; the prevalence and nature of MT applications along with users’ strategies for addressing limitations in MT quality. The conclusions synthesize the research findings, highlighting both the opportunities and the challenges posed by MT in a low-resource language setting like Lithuanian, offering valuable insights for researchers, policymakers, and practitioners in the translation and technology fields.
Translation of culture-specific references (CSRs) is challenging and results in cultural compromises and even untranslatability, especially when cultures are different. The aim of this study is to identify strategies for translating CSRs from Lithuanian into English in tourist-related promotional texts. CSRs were categorised according to their types and translation strategies. The distribution of CSRs was almost proportional in all categories: organisations, material culture, social culture, names, and ecology. The translation strategies included literal translation (dominant), globalisation, preservation, addition, descriptive equivalent, omission and orthographic adaptation. The study contributes to the understanding of intercultural communication in the context of Lithuanian culture.
The major language editor’s role is to enhance the quality of a particular text by correcting language errors and adapting the text according to some formal guidelines. The language editing of a translated text is complicated since many texts, including medical research articles, are translated by non-professional translators, which often results in a low-quality translation forcing the language editor to work hard in order to provide a proper quality to the text. In addition, texts are often translated by writers themselves leaving language editors in a more challenging situation since manuscripts contain abundance of language errors, including those in grammatical and syntactical structures, choice of lexical items, and terminology. The present study analyses a number of medical research articles translated from Lithuanian to English and presented for the publication in an international scientific magazine. The major attention is on the corrections made by a language editor. The most common language mistakes are identified. An assumption is made that the most frequent mistakes will be related to grammar (article usage, number agreement, tenses, word order, prepositions, etc.); however, more corrections are made by a language editor, namely those related to the formal features of the text. The study shows that not all the corrections made by a language editor demonstrate the quality of a text.
Abstract Artificial Intelligence (AI), as a multidisciplinary field, combines computer science, robotics and cognitive science, with increasingly growing applications in many diverse areas, such as engineering, business, medicine, weather forecasting, industry, translation, natural language, linguistics, etc. In Europe, interest in AI has been rising in the last decade. One of the greatest hurdles for researchers in automated processing of technical documentation is large amounts of specific terminology. The aim of this research is to analyse the semi-automatically extracted artificial intelligence-related terminology and the most common phrases related to artificial intelligence in English and Lithuanian in terms of their structure, multidisciplinarity and connotation. For selection and analysis of terms, two programmes were chosen in this study, namely SynchroTerm and SketchEngine . The paper presents the outcomes of an AI terminological project carried out with SynchroTerm and provides an analysis of a special corpus compiled in the field of artificial intelligence using the SketchEngine platform. The analysis of semi-automatic term extraction use and corpus-based techniques for artificial intelligence-related terminology revealed that AI as a specialized domain contains multidisciplinary terminology, and is complex and dynamic. The empiric data shows that the context is essential for the evaluation of the concept under analysis and reveals the different connotation of the term.
Technologies offered and used on the Internet play a significant part in the lives of children; nevertheless, little research has been done on how children view and use machine translation (MT). According to recent literature, there are various benefits to using MT in teaching/learning foreign languages, such as more fluent writing, more effective communication, and fewer errors. Nevertheless, the use of MT in classroom settings is often viewed as problematic by language teachers. Despite the fact that a vast number of students have used MT for various purposes or have tried experimenting with MT for certain academic or entertainment purposes, they seem to have mixed feelings about it. The present qualitative study is based on semi-structured interviews and aims to capture a snapshot of Lithuanian children’s perceptions and awareness of MT technologies. The results of the interviews reveal that children mostly find out about MT as a result of their own efforts and employ MT tools for a variety of purposes; however, at school no systematic guidance and/or support in terms of MT use is provided and children tend to perceive that their teachers generally hold negative attitudes towards MT.
Dar niekada žmonės nėra tiek daug rašę, kiek dabar. Kasdien parašome milijardus el. laiškų, trumpųjų žinučių, komentarų internete, rašome tinklaraščius ir atsiliepimus, kuriose dalijamės naujausiais įvykiais, pasiekimais, mokslo laimėjimais ir idėjomis. O kur dar knygos, žurnalai ir žiniasklaida. Tam, kad būtų skatinama globali sklaida, mažinama mokslinė atskirtis, labai svarbu užtikrinti kokybišką vertimą, plėsti dalykinių tekstų vertimo apimtį ir taikyti naujausias technologijas, kurios, kaip pažymi knygos autorės, „labai paspartina vertimo procesą, tačiau kelia ir naujų iššūkių“. KTU mokslininkės – prof. dr. Ramunė Kasperė, doc. dr. Jurgita Mikelionienė, doc. dr. Dainora Maumevičienė, doktorantė Jurgita Motiejūnienė ir lektorė Dalia Venckienė – parengė išsamų vadovėlį „Vertimas, tekstas, technologijos“, kuriame supažindina skaitytojus su pamatinėmis technikos kalbos vertimo kryptimis, metodais ir kitais aktualiais profesijos aspektais. Mokslinis leidinys skirtas vertimo studijų ir kitų filologijos mokslų krypčių studentams, norintiems atnaujinti ir plėsti savo žinias apie dirbtiniu intelektu grįstą mašininį vertimą, postredagavimą ir lokalizaciją. Vadovėlyje pateikiama informacija bus naudinga ir kitų studijų krypčių studentams, besidomintiems įvairiais vertimo metodais, dalykinių tekstų vertimu, vertimo etika.
