The INTERSPEECH 2020 Computational Paralinguistics Challenge: Elderly Emotion, Breathing & Masks

Schuller, Björn W.; Batliner, Anton; Bergler, Christian; Messner, Eva-Maria; Hamilton, Antonia; Amiriparian, Shahin; Baird, Alice; Rizos, Georgios; Schmitt, Maximilian; Stappen, Lukas; Baumeister, Harald; MacIntyre, Alexis Deighton; Hantke, Simone

doi:10.21437/Interspeech.2020-32

The INTERSPEECH 2020 Computational Paralinguistics Challenge: Elderly Emotion, Breathing & Masks

Björn W. Schuller, Anton Batliner, Christian Bergler, Eva-Maria Messner, Antonia Hamilton, Shahin Amiriparian, Alice Baird, Georgios Rizos, Maximilian Schmitt, Lukas Stappen, Harald Baumeister, Alexis Deighton MacIntyre, Simone Hantke

The INTERSPEECH 2020 Computational Paralinguistics Challenge addresses three different problems for the first time in a research competition under well-defined conditions: In the Elderly Emotion Sub-Challenge, arousal and valence in the speech of elderly individuals have to be modelled as a 3-class problem; in the Breathing Sub-Challenge, breathing has to be assessed as a regression problem; and in the Mask Sub-Challenge, speech without and with a surgical mask has to be told apart. 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 partially add deep end-to-end sequential modelling, and, for the first time in the challenge, linguistic analysis.