Mallol Ragolta, Adrià; Cuesta, Helena; Gómez Gutiérrez, Emilia, 1975-; Schuller, Björn(International Speech Communication Association (ISCA), 2021)
The aim of this contribution is to automatically detect COVID19 patients by analysing the acoustic information embedded in coughs. COVID-19 affects the respiratory system, and, consequently, respiratory-related signals ...
For the last few years, there has been an increasing interest in the estimation of physiological data in the context of human behavior understanding and human computer interaction with many different applications such as ...
Aspandi, Decky; Mallol Ragolta, Adrià; Schuller, Björn; Binefa i Valls, Xavier(Institute of Electrical and Electronics Engineers (IEEE), 2020)
There is a growing interest in affective computing research nowadays given its crucial role in bridging humans with computers. This progress has recently been accelerated due to the emergence of bigger dataset. One recent ...
Mallol Ragolta, Adrià; Cuesta, Helena; Gómez Gutiérrez, Emilia, 1975-; Schuller, Björn(International Speech Communication Association (ISCA), 2022)
This work presents an outer product-based approach to fuse the embedded representations learnt from the spectrograms of cough, breath, and speech samples for the automatic detection of COVID-19. To extract deep learnt ...
