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Heart rate is an important vital sign used in the diagnosis of many medicalconditions. Conventionally, heart rate is measured using a medical device suchas pulse oxymeter. Physiological parameters such as heart rate bear acorrelation to speech characteristics of an individual. Hence, there is apossibility to measure heart rate from speech signals using machine learningand deep learning, which would also allow non-invasive, non contact based andremote monitoring of patients. However, to design such a scheme and verify itsaccuracy, it is necessary to collect speech recordings along with heart ratesmeasured using a medical device, simultaneously during the recording. Thisarticle provides a dataset as well as the procedure used to create the datasetwhich could be used to facilitate research in developing techniques to estimateheart rate accurately by observing speech signal.

Dataset of raw and pre-processed speech signals, Mel Frequency Cepstral Coefficients of Speech and Heart Rate measurements