schuller21@interspeech_2021@ISCA

#1 The INTERSPEECH 2021 Computational Paralinguistics Challenge: COVID-19 Cough, COVID-19 Speech, Escalation & Primates [PDF] [Copy] [Kimi¹]

Authors: Björn W. Schuller ; Anton Batliner ; Christian Bergler ; Cecilia Mascolo ; Jing Han ; Iulia 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 ; Leon J.M. Rothkrantz ; Joeri A. Zwerts ; Jelle Treep ; Casper S. Kaandorp

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, 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.