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2019 INTERSPEECH INTERSPEECH 2019

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

Abstract

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.

🌉 Interdisciplinary Bridge — Deep Learning and Machine Learning
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Speech & Audio
🧭 Keyword Pioneer — sleepiness assessment
🐣 Hot Topic Early Bird — audio classification

Authors

Bjorn 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

Topics

Machine Learning > Core Methods > Classification Machine Learning > Core Methods > Regression Deep Learning > Techniques > Pretraining Speech & Audio > Analysis > Speech Analysis Machine Learning > Learning Types > Classification Machine Learning > Learning Types > Regression

Keywords

representation learning feature extraction speech analysis audio classification dialect classification computational paralinguistics sleepiness assessment
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