  This paper presents a new multimodal interventional radiology dataset, called
PoCaP (Port Catheter Placement) Corpus. This corpus consists of speech and
audio signals in German, X-ray images, and system commands collected from 31
PoCaP interventions by six surgeons with average duration of 81.4 $\pm$ 41.0
minutes. The corpus aims to provide a resource for developing a smart speech
assistant in operating rooms. In particular, it may be used to develop a speech
controlled system that enables surgeons to control the operation parameters
such as C-arm movements and table positions. In order to record the dataset, we
acquired consent by the institutional review board and workers council in the
University Hospital Erlangen and by the patients for data privacy. We describe
the recording set-up, data structure, workflow and preprocessing steps, and
report the first PoCaP Corpus speech recognition analysis results with 11.52
$\%$ word error rate using pretrained models. The findings suggest that the
data has the potential to build a robust command recognition system and will
allow the development of a novel intervention support systems using speech and
image processing in the medical domain.
