no code implementations • ACL (NLP4PosImpact) 2021 • Pierrette Bouillon, Johanna Gerlach, Jonathan Mutal, Nikos Tsourakis, Hervé Spechbach
In this overview article we describe an application designed to enable communication between health practitioners and patients who do not share a common language, in situations where professional interpreters are not available.
no code implementations • EAMT 2020 • Jonathan Mutal, Johanna Gerlach, Pierrette Bouillon, Hervé Spechbach
In diagnostic interviews, elliptical utterances allow doctors to question patients in a more efficient and economical way.
no code implementations • EAMT 2020 • Paula Estrella, Emiliano Cuenca, Laura Bruno, Jonathan Mutal, Sabrina Girletti, Lise Volkart, Pierrette Bouillon
We believe that machine translation (MT) must be introduced to translation students as part of their training, in preparation for their professional life.
no code implementations • SLPAT (ACL) 2022 • Johanna Gerlach, Jonathan Mutal, Bouillon Pierrette
In this study we compare two approaches (neural machine translation and edit-based) and the use of synthetic data for the task of translating normalised Swiss German ASR output into correct written Standard German for subtitles, with a special focus on syntactic differences.
no code implementations • EAMT 2022 • Pierrette Bouillon, Johanna Gerlach, Jonathan Mutal, Marianne Starlander
We present the PASSAGE project, which aims at automatic Standard German subtitling of Swiss German TV content.
no code implementations • AMTA 2022 • Jonathan Mutal, Pierrette Bouillon, Magali Norré, Johanna Gerlach, Lucia Ormaechea Grijalba
The use of images has been shown to positively affect patient comprehension in medical settings, in particular to deliver specific medical instructions.
no code implementations • RANLP 2019 • Jonathan Mutal, Lise Volkart, Pierrette Bouillon, Sabrina Girletti, Paula Estrella
In this study, we compare the output quality of two MT systems, a statistical (SMT) and a neural (NMT) engine, customised for Swiss Post{'}s Language Service using the same training data.