Detection of Mild Dyspnea from Pairs of Speech Recordings

Sander M. Boelders; Venkata Srikanth Nallanthighal; Vlado Menkovski; Aki Härmä

ICASSP 2020accepted0 citations

Detection of Mild Dyspnea from Pairs of Speech Recordings

Sander M. Boelders, Venkata Srikanth Nallanthighal, Vlado Menkovski, Aki Härmä

Abstract

Shortness of breath, or dyspnea is a condition of the cardio-pulmonary system that may be caused by, for example, a heart or lung disease, or physical load. In this paper, we explore techniques of detecting mild dyspnea directly from conversational speech, for example, in a telehealth application. We demonstrate with a collection of speech recordings before and after a light physical exercise that a siamese neural network, when presented examples of the two conditions, can detect the difference between two speech signals. This shows that this signal can be detected using data-pairs, removing the need for ratings of severity or the distinction of separate classes.

BibTeX

@inproceedings{icassp2020_detectionofmildd,
  title = {Detection of Mild Dyspnea from Pairs of Speech Recordings},
  author = {Sander M. Boelders and Venkata Srikanth Nallanthighal and Vlado Menkovski and Aki Härmä},
  booktitle = {ICASSP 2020},
  year = {2020}
}