The INTERSPEECH 2019 Computational Paralinguistics Challenge: Styrian Dialects, Continuous Sleepiness, Baby Sounds & Orca Activity

Schuller, Björn W.; Batliner, Anton; Bergler, Christian; Pokorny, Florian B.; Krajewski, Jarek; Cychosz, Margaret; Vollmann, Ralf; Roelen, Sonja-Dana; Schnieder, Sebastian; Bergelson, Elika; Cristia, Alejandrina; Seidl, Amanda; Warlaumont, Anne S.; Yankowitz, Lisa; Nöth, Elmar; Amiriparian, Shahin; Hantke, Simone; Schmitt, Maximilian

doi:10.21437/Interspeech.2019-1122

The INTERSPEECH 2019 Computational Paralinguistics Challenge: Styrian Dialects, Continuous Sleepiness, Baby Sounds & Orca Activity

Björn W. Schuller, Anton Batliner, Christian Bergler, Florian B. Pokorny, Jarek Krajewski, Margaret Cychosz, Ralf Vollmann, Sonja-Dana Roelen, Sebastian Schnieder, Elika Bergelson, Alejandrina Cristia, Amanda Seidl, Anne S. Warlaumont, Lisa Yankowitz, Elmar Nöth, Shahin Amiriparian, Simone Hantke, Maximilian Schmitt

The INTERSPEECH 2019 Computational Paralinguistics Challenge addresses four different problems for the first time in a research competition under well-defined conditions: In the Styrian Dialects Sub-Challenge, three types of Austrian-German dialects have to be classified; in the Continuous Sleepiness Sub-Challenge, the sleepiness of a speaker has to be assessed as regression problem; in the Baby Sound Sub-Challenge, five types of infant sounds have to be classified; and in the Orca Activity Sub-Challenge, orca sounds have to be detected. We describe the Sub-Challenges and baseline feature extraction and classifiers, which include data-learnt (supervised) feature representations by the ‘usual’ ComParE and BoAWfeatures, and deep unsupervised representation learning using the auDeep toolkit.