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 [BibTeX] [Marc21]
Phoneme based Respiratory Analysis of Read Speech
Type of publication: Conference paper
Citation: Nallanthighal_EUSIPCO_2021
Publication status: Accepted
Booktitle: Proceedings of European Signal Processing Conference (EUSIPCO)
Year: 2021
Abstract: Recent work shows that it is possible to use deep learning techniques to sense the speaker’s respiratory parameters di- rectly from a speech signal. This can be a beneficial option for future telehealth services. In this paper, we dive deeper and study how respiratory effort depends on the linguistic content of the speech utterance. This is obtained by analysis of respi- ratory belt sensor data and phoneme-aligned speech data. The results show, for example, that the respiratory effort was high- est for fricatives, compared to other broad phonetic classes, and especially high for the glottal consonants. The insights may help to develop more efficient protocols for respiratory health monitoring in telehealth applications.
Projects Idiap
Authors Nallanthighal, Venkata Srikanth
Härmä, Aki
Strik, Helmer
Magimai.-Doss, Mathew
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Total mark: 0
  • Nallanthighal_EUSIPCO_2021.pdf