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The INTERSPEECH 2018 Computational Paralinguistics Challenge: Atypical & Self-Assessed Affect, Crying & Heart Beats

Year: 2018
Type: conference-paper
Abstract: The INTERSPEECH 2018 Computational Paralinguistics Challenge addresses four different problems for the first time in a research competition under well-defined conditions: In the Atypical Affect Sub-Challenge, four basic emotions annotated in the speech of handicapped subjects have to be classified; in the Self-Assessed Affect Sub-Challenge, valence scores given by the speakers themselves are used for a three-class classification problem; in the Crying Sub-Challenge, three types of infant vocalisations have to be told apart; and in the Heart Beats Sub-Challenge, three different types of heart beats have to be determined.We describe the Sub-Challenges, their conditions, and baseline feature extraction and classifiers, which include data-learnt (supervised) feature representations by end-to-end learning, the 'usual' ComParE and BoAW features, and deep unsupervised representation learning using the AUDEEP toolkit for the first time in the challenge series.
DOI: 10.21437/interspeech.2018-51
Authors: Björn Schuller, Stefan Steidl, Anton Batliner, Peter B. Marschik, Harald Baumeister, Fengquan Dong, Simone Hantke, Florian B. Pokorny, Eva-Maria Rathner, Katrin D. Bartl-Pokorny, Christa Einspieler, Dajie Zhang, Alice Baird, Shahin Amiriparian, Kun Qian, Zhao Ren, Maximilian Schmitt, Panagiotis Tzirakis, Stefanos Zafeiriou
Institutions: University of Augsburg, Imperial College London, Friedrich-Alexander-Universität Erlangen-Nürnberg, Medical University of Graz, Karolinska Institutet, Universitätsmedizin Göttingen, Universität Ulm, Shenzhen University, Technical University of Munich, University of Oulu
Language: English
Field: Psychology
Open Access status: green
OpenAlex ID: W2889342907
FWCI: 20.71
Cites: 29
Cited by: 105
Related to: 10