PoCaP Corpus: A Multimodal Dataset for Smart Operating Room Speech Assistant using Interventional Radiology Workflow Analysis

TL;DR

The PoCaP Corpus is a multimodal dataset combining speech, audio, X-ray images, and system commands from interventional radiology procedures, designed to enable development of smart speech assistants for operating rooms.

Contribution

This work introduces the first multimodal PoCaP Corpus for interventional radiology, facilitating research on speech-controlled surgical systems and workflow analysis.

Findings

Achieved 11.52% word error rate in speech recognition

Demonstrated dataset's potential for robust command recognition

Enabled development of intervention support systems

Abstract

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.