In the Human-Machine Communication professorship, we conduct research on the interaction between language and technology. Among other things, we investigate the potential and challenges of machine translation systems in everyday life. In doing so, our goal is to find out how artificial communication can help to shape the communication of tomorrow and where human thinking is essential. Such findings act as a catalyst for advancing research because they form the basis for more human-friendly AI systems on the one hand and more machine-friendly work and communication processes on the other. This knowledge is a helpful resource for both the professional world and society as a whole as it allows for communication and language experts to be equipped with the best tools and thus help to shape the increasing trade-off between internationalisation and localisation in a professional and efficient manner.
As digitalisation progresses, new technologies such as machine translation (MT) may present new opportunities, perspectives and risks for tertiary education. In the areas of research and teaching, however, it is becoming apparent that students and lecturers are often unaware of how to use the available tools, meaning they are unable to exploit their full potential. The DigLit project, which is jointly financed by swissuniversities and the partner institutions, is addressing this issue.
Machine translation for crisis communication
This project investigates how machine translation services can help employees from administrations, NGOs and education to communicate with refugees. Providing public services to newly arrived refugees is a linguistic challenge: interprets are expensive and not available for all languages. Although machine ...
Machine Subtitling of Videos
We investigate if and how the quality of video subtitles generated by AI-based technology (i.e. transcription and machine translation of spoken language) can be scored automatically.
Machine translation for academic texts
The project consists in developing a prototype for a ZHAW neural machine translation system trained on academic texts. Freely accessible systems such as DeepL and Google Translate are not specifically trained on scientific texts and therefore often present issues regarding terminology, text cohesion, pragmatics and ...
In the BA in Multilingual Communication, the MA in Applied Linguistics and the doctoral programme, we offer different modules with content from the area of human-machine communication, including the following:
- Applied linguistics for language professions: automated text translation
- Communication studies seminar: the language industry of the future
- PhD seminar: AI and language: what neural machine translation teaches us about communicating through algorithms
We also supervise theses in topics such as those mentioned above.