PoCaP语料库:基于介入放射学工作流程分析的智能手术室语音助手多模态数据集

K. Demir, M. May, A. Schmid, M. Uder, K. Breininger, T. Weise, A. Maier, Seung Hee Yang
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引用次数: 2

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。该语料库包括德语语音和音频信号、x射线图像和系统命令,这些数据来自6位外科医生平均81次的31次PoCaP干预。4±41。0分钟。该语料库旨在为手术室智能语音助手的开发提供资源。特别是,它可以用来开发一种语音控制系统,使外科医生能够控制手术参数,如c型臂运动和桌子位置。为了记录数据集,我们获得了埃尔兰根大学医院机构审查委员会和工人委员会以及患者的同意,以保护数据隐私。我们描述了记录设置、数据结构、工作流程和预处理步骤,并报告了首次使用预训练模型的PoCaP语料库语音识别分析结果,错误率为11.52%。研究结果表明,这些数据有可能建立一个强大的命令识别系统,并将允许在医疗中使用语音和图像开发一种新的干预支持系统
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PoCaP Corpus: A Multimodal Dataset for Smart Operating Room Speech Assistant using Interventional Radiology Workflow Analysis
. 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 ± 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 in the medical
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