In emergency care settings, there is a crucial need for automated translation tools. We focus here on the BabelDr system, a speech-enabled fixed-phrase translator used to improve communication in emergency settings between doctors and allophone patients. The aim of the chapter is two-fold. First, we will assess if a bidirectional version of the phraselator allowing patients to answer doctors’ questions by selecting pictures from open-source databases will improve user satisfaction. Second, we wish to evaluate pictograph usability in this context. Our hypotheses are that images will in fact help to improve patient satisfaction and that multiple factors influence pictograph usability. Factors of interest include not only the comprehensibility of the pictographs per se, but also how the images are presented to the user with respect to their number and ordering. We showed that most respondents prefer to use the interface with pictographs and that multiple factors influence participants’ ability to find a pictograph based on a written form, but that the comprehensibility of the individual pictographs is probably the most important.

Access to healthcare profoundly impacts the health and quality of life of Deaf people. Automatic translation tools are crucial in improving communication between Deaf patients and their healthcare providers. The aim of this chapter is to present the pipeline used to create the Swiss-French Sign Language (LSF-CH) version of BabelDr, a speech-enabled fixed phrase translator that was initially conceived to improve communication in emergency settings between doctors and allophone patients (Bouillon et al., 2021). In order to do so, we start off by explaining how we ported BabelDr in LSF-CH using both human and avatar videos. We first describe the creation of a reference corpus consisting of video translations done by human translators, then we present a second corpus of videos generated with a virtual human. Finally, we relate the findings of a questionnaire on Deaf users’ perspective on the use of signing avatars in the medical context. We showed that, although respondents prefer human videos, the use of automatic technologies associated with virtual characters is not without interest to the target audience and can be useful to them in the medical context.