Artificial intelligence-grounded machine translation has fundamentally changed public awareness and attitudes towards multilingual communication. In some language pairs, the accuracy, quality and efficiency of machine-translated texts of certain types can be quite high. Hence, the end-user acceptability and reliance on machine-translated content could be justified. However, machine translation in small and/or low-resource languages might yield significantly lower quality, which in turn may lead to potentially negative consequences and risks if machine translation is used in high-risk contexts without awareness of the drawbacks, critical assessment and modifications to the raw output. The current study, which is part of a more extensive project focusing on the societal impact of machine translation, is aimed at revealing the attitudes towards usability and quality as perceived from the end-user perspective. The research questions addressed revolve around the machine translation types used, purposes of using machine translation, perceived quality of the generated output, and actions taken to improve the quality by users with various backgrounds. The research findings rely on a survey of the population (N = 402) conducted in 2021 in Lithuania. The study reveals the frequent use of machine translation for a diversity of purposes. The most common uses include work, research and studies, and household environments. A higher level of education correlates with user dissatisfaction with the generated quality and actions taken to improve it. The findings also reveal that age correlates with the use of machine translation. Sustainable measures to reduce machine translation related risks have to be established based on the perceptions of different social groups in different societies and cultures.
It has been proven in many quality-focused studies that machine translation output in some language pairs is still far from publishable (Koponen, 2016). Even so, post-editing has become a daily practice among translators and translation service providers, especially with language pairs where machine translation demonstrates good human parity. The fast development of machine translation and its quality improvement have led to a growing demand of post-editors. This study attempts to evaluate the quality of the most popular machine translation tools for the Lithuanian language in order to find the correlation between the results of automatic quality estimation (i.e., the BLUE score), human / manual evaluation of machine translation output quality following the multidimensional quality metrics (MQM) and the most common machine translation engines used by freelancers and language service providers. The conclusions are based on the findings of a survey and the automatic vs human / manual machine translation quality analysis. The findings demonstrate and support previous research that automatic machine translation quality estimation may not be taken for granted. Human / manual machine translation quality evaluation is still a better indicator whether a machine translation tool fits the purpose of translation. The study brings to the fore some insightful findings that may be beneficial for translator and post-editor trainers from the pedagogical perspective as well as for translation industry from the practical perspective.
State-of-the-art research shows that the impact of language technologies on public awareness and attitudes toward using machine translation has been changing. As machine translation acceptability is considered to be a multilayered concept, this paper employs criteria of usability, satisfaction and quality as components of acceptability measurement. The study seeks to determine whether there are any differences in the machine-translation acceptability between professional users, i.e., translators and language editors, and non-professional users, i.e., ordinary users of machine translation who use it for non-professional everyday purposes. The main research questions whether non-professional users process raw machine translation output in the same way as professional users and whether there is a difference in the processing of raw machine-translated output between users with different levels of machine-translated text acceptability are analyzed. The results of an eye tracking experiment, measuring fixation time, dwell time and glance count, indicate a difference between professional and non-professional users' cognitive processing and acceptability of machine translation output: translators and language editors spend more time overall reading the machine-translated texts, possibly because of their deeper critical awareness as well as professional attitude toward the text. In terms of acceptability overall, professional translators critically assess machine translation on all components of which confirms the findings of previous similar research. However, the study draws attention to non-professional users' lower awareness regarding machine translation quality. The study was conducted within a research project that received funding from the Research Council of Lithuania (LMTLT, agreement No S-MOD-21-2), seeking to explore and evaluate the impact on society of machine translation technological solutions.
The article deals with the specifics of the verbal implementation of prohibitions and restrictions in quarantine-epidemiological texts. The object is the category of prohibition, the subject is the specifics of the verbalization of this category, namely the structural and semantic content, pragmatic and discursive features of the functioning of the verbal representatives of the semantics of the prohibition. The actual material for this paper is the texts of informational messages in the Ukrainian language, which refer to the prohibition on visiting public places without protective masks. Lexical, syntactic, graphic means of textual organization of prohibition announcements were studied. Special attention is paid to the categories of addressant and addressee, methods of explication of these discursive elements, specific creolization of the studied advertisement texts.
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