论文标题
POCAP语料库：使用介入放射学工作流程分析的智能手术室语音助手的多模式数据集
PoCaP Corpus: A Multimodal Dataset for Smart Operating Room Speech Assistant using Interventional Radiology Workflow Analysis
论文作者
论文摘要
本文提出了一个新的多模式介入放射学数据集，称为POCAP（端口导管放置）语料库。该语料库由德语，X射线图像的语音和音频信号组成，以及六位外科医生从31个POCAP干预收集的系统命令，平均持续时间为81.4 $ \ pm $ 41.0分钟。该语料库旨在为在手术室中开发智能演讲助理提供资源。特别是，它可用于开发语音控制的系统，该系统使外科医生能够控制CARM运动和表位置等操作参数。为了记录数据集，我们获得了Erlangen大学医院和患者数据隐私的机构审查委员会和工人委员会的同意。我们描述了录制设置，数据结构，工作流程和预处理步骤，并使用预告片的模型以11.52 $ \％$单词错误率报告了第一个POCAP语料库语音识别分析结果。研究结果表明，数据有可能建立强大的命令识别系统，并将使用医学领域中的语音和图像处理来开发新颖的干预支持系统。
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.
