COVYT: Introducing the Coronavirus YouTube and TikTok speech dataset featuring the same speakers with and without infection

no code implementations • 20 Jun 2022 • Andreas Triantafyllopoulos, Anastasia Semertzidou, Meishu Song, Florian B. Pokorny, Björn W. Schuller

As compared to other existing COVID-19 sound datasets, the unique feature of the COVYT dataset is that it comprises both COVID-19 positive and negative samples from all 65 speakers.

Climate Change & Computer Audition: A Call to Action and Overview on Audio Intelligence to Help Save the Planet

no code implementations • 10 Mar 2022 • Björn W. Schuller, Alican Akman, Yi Chang, Harry Coppock, Alexander Gebhard, Alexander Kathan, Esther Rituerto-González, Andreas Triantafyllopoulos, Florian B. Pokorny

We categorise potential computer audition applications according to the five elements of earth, water, air, fire, and aether, proposed by the ancient Greeks in their five element theory; this categorisation serves as a framework to discuss computer audition in relation to different ecological aspects.

Fitbeat: COVID-19 Estimation based on Wristband Heart Rate

no code implementations • 19 Apr 2021 • Shuo Liu, Jing Han, Estela Laporta Puyal, Spyridon Kontaxis, Shaoxiong Sun, Patrick Locatelli, Judith Dineley, Florian B. Pokorny, Gloria Dalla Costa, Letizia Leocan, Ana Isabel Guerrero, Carlos Nos, Ana Zabalza, Per Soelberg Sørensen, Mathias Buron, Melinda Magyari, Yatharth Ranjan, Zulqarnain Rashid, Pauline Conde, Callum Stewart, Amos A Folarin, Richard JB Dobson, Raquel Bailón, Srinivasan Vairavan, NIcholas Cummins, Vaibhav A Narayan, Matthew Hotopf, Giancarlo Comi, Björn Schuller

This study investigates the potential of deep learning methods to identify individuals with suspected COVID-19 infection using remotely collected heart-rate data.

Specificity

The voice of COVID-19: Acoustic correlates of infection

no code implementations • 17 Dec 2020 • Katrin D. Bartl-Pokorny, Florian B. Pokorny, Anton Batliner, Shahin Amiriparian, Anastasia Semertzidou, Florian Eyben, Elena Kramer, Florian Schmidt, Rainer Schönweiler, Markus Wehler, Björn W. Schuller

Group differences in the front vowels /i:/ and /e:/ are additionally reflected in the variation of the fundamental frequency and the harmonics-to-noise ratio, group differences in back vowels /o:/ and /u:/ in statistics of the Mel-frequency cepstral coefficients and the spectral slope.