论文标题
原始和预处理的语音信号，MEL频率的语音系数和心率测量的数据集
Dataset of raw and pre-processed speech signals, Mel Frequency Cepstral Coefficients of Speech and Heart Rate measurements
论文作者
论文摘要
心率是用于诊断许多医疗状况的重要生命体征。通常，心率是使用医疗装置（例如脉搏氧气表）测量的。诸如心率之类的生理参数与个人的语音特征有关联。因此，有可能使用机器学习和深度学习来衡量语音信号的心率，这也将允许对患者进行非侵入性，非接触性和远程监测。但是，要设计这样的方案并验证其准确性，有必要在记录期间同时收集语音记录以及使用医疗设备测量的心率。本文提供了一个数据集以及用于创建数据集的过程，该数据集可用于促进开发技术研究以通过观察语音信号准确估算心率的研究。
Heart rate is an important vital sign used in the diagnosis of many medical conditions. Conventionally, heart rate is measured using a medical device such as pulse oxymeter. Physiological parameters such as heart rate bear a correlation to speech characteristics of an individual. Hence, there is a possibility to measure heart rate from speech signals using machine learning and deep learning, which would also allow non-invasive, non contact based and remote monitoring of patients. However, to design such a scheme and verify its accuracy, it is necessary to collect speech recordings along with heart rates measured using a medical device, simultaneously during the recording. This article provides a dataset as well as the procedure used to create the dataset which could be used to facilitate research in developing techniques to estimate heart rate accurately by observing speech signal.
