The INTERSPEECH 2021 Computational Paralinguistics Challenge: COVID-19 Cough, COVID-19 Speech, Escalation & Primates
Schuller, Björn W.; Batliner, Anton; Bergler, Christian; Mascolo, Cecilia; Han, Jing; Lefter, Iulia; Kaya, Heysem; Amiriparian, Shahin; Baird, Alice; Stappen, Lukas; Ottl, Sandra; Gerczuk, Maurice; Tzirakis, Panagiotis; Brown, Chloë; Chauhan, Jagmohan; Grammenos, Andreas; Hasthanasombat, Apinan; Spathis, Dimitris; Xia, Tong; Cicuta, Pietro; Rothkrantz, Leon J.m.; Zwerts, Joeri A.; Treep, Jelle; Kaandorp, Casper S.
(2021) INTERSPEECH 2021, pp. 431 - 435
(Contribution to conference)
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 Sub- Challenge,
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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 'usual' 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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Keywords: COVID-19, Challenge, Computational paralinguistics, Escalation, Primates, Language and Linguistics, Human-Computer Interaction, Signal Processing, Software, Modelling and Simulation
Note: Funding Information: We acknowledge funding from the DFG’s Reinhart Koselleck project No. 442218748 (AUDI0NOMOUS), the EU’s HORIZON 2020 Grant No. 115902 (RADAR CNS), and the ERC project No. 833296 (EAR). Publisher Copyright: Copyright © 2021 ISCA.