Accessibility and inclusion have become key terms of the last decades, and this does not exclude linguistics. Machine-translated subtitling has become the new approach to over-come linguistic accessibility barriers since it has proven to be fast and thus cost-efficient for audiovisual media, as opposed to human translation, which is time-intensive and costly. Machine translation can be considered as a solution when a translation is urgently needed. Overall, studies researching benefits of subtitling yield different results, also always depending on the application context (see Chan et al. 2022, Hu et al. 2020). Still, the acceptance of machine-translated subtitles is limited (see Tuominen et al., 2023) and users are rather skeptical, especially regarding the quality of MT subtitles. In the presented project, I investigated the effects of machine-translated subtitling (raw machine translation) compared to human-translated subtitling on the consumer, presenting the results of a case study, knowing that HT as the gold standard for translation is more and more put into question and being aware of today’s convincing output of NMT. The presented study investigates the use of (machine-translated) subtitles by the average consumer due to the current strong societal interest. I base my research project on the 3 R concept, i.e. response, reaction, and repercussion (Gambier, 2009), in which participants were asked to watch two video presentations on educational topics, one in German and another in Finnish, subtitled either with machine translation or by a human translator, or in a mixed condition (machine-translated and human-translated). Subtitle languages are English, German, and Finnish. Afterwards, they were asked to respond to questions on the video content (information retrieval) and evaluate the subtitles based on the User Experience Questionnaire (Laugwitz et al., 2008) and NASA Task Load Index (NASA, 2006). The case study shows that information retrieval in the HT conditions is higher, except for the direction Finnish-German. However, users generally report a better user experience for all lan-guages, which indicates a higher immersion. Participants also report that long subtitles combined with a fast pace contribute to more stress and more distraction from the other visual elements. Generally, users recognise the potential of MT subtitles, but also state that a human-in-the-loop is still needed to ensure publishable quality. References: Chan, Win Shan, Jan-Louis Kruger, and Stephen Doherty. 2022. ‘An Investigation of Subtitles as Learning Support in University Education’. Journal of Specialised Translation, no. 38: 155–79. Gambier, Yves. 2009. ‘Challenges in Research on Audiovisual Translation.’ In Translation Research Projects 2, edited by Pym, Anthony and Alexander Perekrestenko, 17–25. Tarragona: Intercultural Studies Group. Hu, Ke, Sharon O’Brien, and Dorothy Kenny. 2020. ‘A Reception Study of Machine Translated Subtitles for MOOCs’. Perspectives 28 (4): 521–38. https://doi.org/10.1080/0907676X.2019.1595069. Laugwitz, Bettina, Theo Held, and Martin Schrepp. 2008. ‘Construction and Evaluation of a User Experience Questionnaire’. In Symposium of the Austrian HCI and Usability Engineering Group, edited by Andreas Holzinger, 63–76. Springer. NASA. 2006. ‘NASA TLX: Task Load Index’. Tuominen, Tiina, Maarit Koponen, Kaisa Vitikainen, Umut Sulubacak, and Jörg Tiedemann. 2023. ‘Exploring the Gaps in Linguistic Accessibility of Media: The Potential of Automated Subtitling as a Solution’. Journal of Specialised Translation, no. 39: 77–89.