Speaker
Description
According to recent studies in the field of Public Health, over half of the German population indicates having difficulties finding, comprehending, appraising and using health-related information (Schaeffer et al. 2021). The German National Action Plan Health Literacy lists Plain Language as a communicative tool to make health information more accessible to large population groups (Schaeffer et al. 2018). There is a high demand for comprehensibility-enhanced health communication, but few translation resources (Maaß 2020).
To meet the demand for interlingual translations, meaning the translation between natural languages, AI-based translation tools have long been adopted into the interlingual translation process. In intralingual translation, i. e. the translation from one language variety to another, translation tools are still missing. AI-based intralingual machine translation represents a promising tool to support the production of comprehensible texts in the field of health communication (Deilen et al. 2024a, 2024b), but there are numerous research desiderata regarding its implementation, quality of outputs, and post-editing processes.
The project KI-gestützte Gesundheitskommunikation (KI-GesKom, AI-supported health communication) is a cooperation between the Research Centre for Easy Language, the German health magazine Apotheken Umschau and SUMM AI. Using the AI-based machine translation tool SUMM AI, we compare machine generated Plain Language translations with their source texts and with professionally translated Plain Language texts. We propose a poster to present the research design and results on the levels 1) correctness, 2) readability, and 3) syntactical complexity (Deilen et al. 2023; Deilen et al. 2024a). In terms of correctness, AI-translated texts need (often extensive) post-editing. The analyses reveal not only spelling errors, but also content-related mistakes like incorrect statements or explanations (Deilen et al. 2024b). AI-generated texts have a higher readability than professional translations, but are more syntactically complex (Deilen et al. 2024a). We conclude that AI-based translation tools are useful for the intralingual translation process. However, the translation tools need adequate training data, and the AI-generated texts need to be professionally post-edited.
Literature
Deilen, Silvana; Hernández Garrido, Sergio; Lapshinova-Koltunski, Ekaterina; Maaß, Christiane (2023): Using ChatGPT as a CAT tool in Easy Language translation. In: Štajner, Sanja; Saggio, Horacio; Shardlow, Matthew & Alva-Manchego, Fernando (Hrsg.): Proceedings of the Second Workshop on Text Simplification, Accessibility and Readability (TSAR). Shoumen, Bulgaria: INCOMA Ltd., 1–10.
Deilen, Silvana; Lapshinova-Koltunski, Ekaterina; Hernández Garrido, Sergio; Maaß, Christiane; Hörner, Julian; Theel, Vanessa; Ziemer, Sopie (2024a): Evaluation of intralingual machine translation for health communication. In: Song, Xingyi; Gow-Smith, Edward; Scarton, Carolina; Cabarrão, Vera; Chatzitheodorou, Konstantinos; Cadwell, Patrick; Lapshinova-Koltunski, Ekaterina; Bawden, Rachel; Sánchez-Cartagena, Víctor M.; Haddow, Barry; Kanojia, Diptesh; Nurminen, Mary; Moniz, Helena; Forcada, Mikel & Oakley, Chris (Hrsg.): Proceedings of the 25th Annual Conference of the European Association for Machine Translation: Volume 1: Research And Implementations & Case Studies. Sheffield: European Association for Machine Translation (EAMT), 467–477.
Deilen, Silvana; Lapshinova-Koltunski, Ekaterina; Hernández Garrido, Sergio; Maaß, Christiane; Hörner, Julian; Theel, Vanessa; Ziemer, Sopie (2024b): Towards AI-supported Health Communication in Plain Language: Evaluating Intralingual Machine Translation of Medical Texts. In: Demner-Fushman, Dina; Ananiadou, Sophia; Thompson, Paul & Ondov, Brian (Hrsg.): Proceedings of the First Workshop on Patient-Oriented Language Processing @LREC-COLING-2024 (CL4Health): Workshop Proceedings, 44–53.
Maaß, Christiane (2020): Easy language – plain language – easy language plus: Balancing comprehensibility and acceptability. Berlin: Frank & Timme.
Schaeffer, Doris/Berens, Eva-Maria/Gille, Svea/Griese, Lennert/Klinger, Julia/Sombre, Steffen de/Vogt, Dominique/Hurrelmann, Klaus (2021): Gesundheitskompetenz der Bevölkerung in Deutschland vor und während der Corona Pandemie: Ergebnisse des HLS-GER 2: Universität Bielefeld, Interdisziplinäres Zentrum für Gesundheitskompetenzforschung.
Schaeffer, Doris/Hurrelmann, Klaus/Bauer, Ulrich/Kolpatzik, Kai (2018): National Action Plan Health Literacy. Promoting health literacy in Germany. Berlin: KomPart.
