@inproceedings{merkel-etal-2026-making,
title = "Making Jobs Accessible through {AI}-supported Easy Language Translation",
author = {Merkel, Fabian and
Baumgartner, Marco and
Breskas, Athanasios and
Gierke, Lea and
Gutermuth, Silke and
Hansen-Schirra, Silvia and
Kick, Elena and
K{\"o}nig, Vanessa and
Kopp, Tobias and
Martin, Natalie and
Spie{\ss}, Miriam},
editor = "Shterionov, Dimitar and
Vanmassenhove, Eva and
De Sisto, Mirella and
Blain, Fred and
Pourmostafa Roshan Sharami, Javad and
Lepp, Lisa and
Manna, Chiara and
Rescigno, Argentina Anna and
Karakanta, Alina and
Rigouts Terryn, Ayla and
Lardelli, Manuel and
Resende, Natalia and
Murgolo, Elena and
Hackenbuchner, Jani{\c{c}}a and
Zaretskaya, Anna and
Espl{\`a}-Gomis, Miquel and
Etchegoyhen, Thierry and
Gromann, Dagmar and
Bawden, Rachel and
Haddow, Barry and
Szoc, Sara and
Forcada, Mikel and
Moniz, Helena",
booktitle = "Proceedings of the 26th Annual Conference of the {E}uropean Association for Machine Translation (Volume 2)",
month = jun,
year = "2026",
address = "Tilburg, The Netherlands",
publisher = "European Association for Machine Translation",
url = "https://aclanthology.org/2026.eamt-2.19/",
pages = "39--40",
ISBN = "9789403901404",
abstract = "Access to the primary labor market for people with cognitive impairments is hampered by barriers, notably the lack of workplace information in Easy Language (EL). Producing such texts is time- and cost-intensive and requires specialized translators. The project STARK-LS (Strengthening participation in the primary labor market through AI-generated Easy Language) addresses this gap by implementing an AI-translation tool to translate workplace materials into EL and embedding the approach in internships for people with cognitive impairments. An interdisciplinary project team conducts mixed-methods evaluations by testing the EL translations for applicability, comprehensibility, and acceptance using lab-based eye-tracking and questionnaire studies, qualitative interviews with interns with cognitive impairments and experts for EL, and a quantitative online survey with company representatives. The findings will lead to process models and best-practice recommendations for companies and rehabilitation agencies. The project advances scientific understanding of the perceived usefulness and potential barriers of EL in organizational contexts, while critically evaluating AI{'}s influence on the diffusion of high-quality EL texts in companies. Funded by the German Federal Ministry of Labour and Social Affairs, the project aims to scale high-quality accessible communication and promote sustainable inclusion in the German labor market."
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%0 Conference Proceedings
%T Making Jobs Accessible through AI-supported Easy Language Translation
%A Merkel, Fabian
%A Baumgartner, Marco
%A Breskas, Athanasios
%A Gierke, Lea
%A Gutermuth, Silke
%A Hansen-Schirra, Silvia
%A Kick, Elena
%A König, Vanessa
%A Kopp, Tobias
%A Martin, Natalie
%A Spieß, Miriam
%Y Shterionov, Dimitar
%Y Vanmassenhove, Eva
%Y De Sisto, Mirella
%Y Blain, Fred
%Y Pourmostafa Roshan Sharami, Javad
%Y Lepp, Lisa
%Y Manna, Chiara
%Y Rescigno, Argentina Anna
%Y Karakanta, Alina
%Y Rigouts Terryn, Ayla
%Y Lardelli, Manuel
%Y Resende, Natalia
%Y Murgolo, Elena
%Y Hackenbuchner, Janiça
%Y Zaretskaya, Anna
%Y Esplà-Gomis, Miquel
%Y Etchegoyhen, Thierry
%Y Gromann, Dagmar
%Y Bawden, Rachel
%Y Haddow, Barry
%Y Szoc, Sara
%Y Forcada, Mikel
%Y Moniz, Helena
%S Proceedings of the 26th Annual Conference of the European Association for Machine Translation (Volume 2)
%D 2026
%8 June
%I European Association for Machine Translation
%C Tilburg, The Netherlands
%@ 9789403901404
%F merkel-etal-2026-making
%X Access to the primary labor market for people with cognitive impairments is hampered by barriers, notably the lack of workplace information in Easy Language (EL). Producing such texts is time- and cost-intensive and requires specialized translators. The project STARK-LS (Strengthening participation in the primary labor market through AI-generated Easy Language) addresses this gap by implementing an AI-translation tool to translate workplace materials into EL and embedding the approach in internships for people with cognitive impairments. An interdisciplinary project team conducts mixed-methods evaluations by testing the EL translations for applicability, comprehensibility, and acceptance using lab-based eye-tracking and questionnaire studies, qualitative interviews with interns with cognitive impairments and experts for EL, and a quantitative online survey with company representatives. The findings will lead to process models and best-practice recommendations for companies and rehabilitation agencies. The project advances scientific understanding of the perceived usefulness and potential barriers of EL in organizational contexts, while critically evaluating AI’s influence on the diffusion of high-quality EL texts in companies. Funded by the German Federal Ministry of Labour and Social Affairs, the project aims to scale high-quality accessible communication and promote sustainable inclusion in the German labor market.
%U https://aclanthology.org/2026.eamt-2.19/
%P 39-40
Markdown (Informal)
[Making Jobs Accessible through AI-supported Easy Language Translation](https://aclanthology.org/2026.eamt-2.19/) (Merkel et al., EAMT 2026)
ACL
- Fabian Merkel, Marco Baumgartner, Athanasios Breskas, Lea Gierke, Silke Gutermuth, Silvia Hansen-Schirra, Elena Kick, Vanessa König, Tobias Kopp, Natalie Martin, and Miriam Spieß. 2026. Making Jobs Accessible through AI-supported Easy Language Translation. In Proceedings of the 26th Annual Conference of the European Association for Machine Translation (Volume 2), pages 39–40, Tilburg, The Netherlands. European Association for Machine Translation.