2026-05-19 –, Joost den Draaijer
At University of Applied Sciences Utrecht (HU), we are exploring the use of Whisper, an open-source speech-to-text model from OpenAI, for automatically transcribing research interviews and other audio sources. A key advantage of Whisper is that it can be hosted within our own infrastructure, eliminating the need to share sensitive research data with external commercial parties. Integration with SURF Research Drive also allows transcription data to be stored centrally and securely, without duplication.
In this interactive session, we will share our practical experiences setting up a Whisper-based transcription solution within the SURF Research Cloud. At the end of last year, we assessed the need for a transcription tool for researchers within HU University of Applied Sciences. There was a need. In the spring of 2026, we conducted a short proof of concept.
To avoid having to host the model ourselves, we subsequently joined the SURF AI-hub pilot, a potential new SURF service that makes open-source AI models available via an API. Our case study within this pilot is transcribing audio with Whisper.
During the session, we will demonstrate our technical setup, the choices we made, and the lessons learned. We will also discuss the next steps: a broader experiment with researchers.
The session is intended to share experiences and explore together how AI transcription can be deployed safely and practically within practice-oriented research environments.
Researchers, IT supporters
What is the key take away of your session?:Participants will discover how speech-to-text AI can be applied practically and responsibly in research processes, and which technical and organizational choices are important in this regard.
Stef de Groot, a research engineer at HU University of Applied Sciences, has experience developing applications for various research purposes. He also manages HU University of Applied Sciences' VRE.
Sander Vlugter 31, Research Engineer DevOps.
Hogeschool Utrecht - Team Research Support & IT.
In my role I support researchers across my organization by helping them design, develop, and scale research software and computational workflows. My work includes advising on coding challenges, enabling the use of platforms such as Research Cloud, and helping researchers navigate technical and infrastructure needs so they can focus on their projects. Alongside this, I contribute to strengthening the organization’s research ecosystem by administering the GitHub research organization, supporting SRAM processes, and guiding Research Software Management Plans—while continuously identifying opportunities to improve collaboration, reproducibility, and the sustainability of research software.