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The INTERSPEECH 2021 Computational Paralinguistics Challenge: COVID-19 Cough, COVID-19 Speech, Escalation & Primates

24 February 2021
Björn W. Schuller
A. Batliner
Christian Bergler
Cecilia Mascolo
Jing Han
I. Lefter
Heysem Kaya
Shahin Amiriparian
Alice Baird
Lukas Stappen
Sandra Ottl
Maurice Gerczuk
Panagiotis Tzirakis
Chloë Brown
Jagmohan Chauhan
Andreas Grammenos
Apinan Hasthanasombat
Dimitris Spathis
Tong Xia
Pietro Cicuta
L. Rothkrantz
J. Zwerts
Jelle Treep
Casper S. Kaandorp
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Abstract

The INTERSPEECH 2021 Computational Paralinguistics Challenge addresses four different problems for the first time in a research competition under well-defined conditions: In the COVID-19 Cough and COVID-19 Speech Sub-Challenges, a binary classification on COVID-19 infection has to be made based on coughing sounds and speech; in the Escalation SubChallenge, a three-way assessment of the level of escalation in a dialogue is featured; and in the Primates Sub-Challenge, four species vs background need to be classified. We describe the Sub-Challenges, baseline feature extraction, and classifiers based on the úsual' COMPARE and BoAW features as well as deep unsupervised representation learning using the AuDeep toolkit, and deep feature extraction from pre-trained CNNs using the Deep Spectrum toolkit; in addition, we add deep end-to-end sequential modelling, and partially linguistic analysis.

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