The ACM Multimedia 2022 Computational Paralinguistics Challenge: Vocalisations, Stuttering, Activity, & Mosquitoes
Abstract
The ACM Multimedia 2022 Computational Paralinguistics Challenge addresses four different problems for the first time in a research competition under well-defined conditions: In the Vocalisations and Stuttering Sub-Challenges, a classification on human non-verbal vocalisations and speech has to be made; the Activity Sub-Challenge aims at beyond-audio human activity recognition from smartwatch sensor data; and in the Mosquitoes Sub-Challenge, mosquitoes need to be detected. We describe the Sub-Challenges, baseline feature extraction, and classifiers based on the usual ComPaRE and BoAW features, the auDeep toolkit, and deep feature extraction from pre-trained CNNs using the DeepSpectRum toolkit; in addition, we add end-to-end sequential modelling, and a log-mel-128-BNN.
Keywords
Cite
@article{arxiv.2205.06799,
title = {The ACM Multimedia 2022 Computational Paralinguistics Challenge: Vocalisations, Stuttering, Activity, & Mosquitoes},
author = {Björn W. Schuller and Anton Batliner and Shahin Amiriparian and Christian Bergler and Maurice Gerczuk and Natalie Holz and Pauline Larrouy-Maestri and Sebastian P. Bayerl and Korbinian Riedhammer and Adria Mallol-Ragolta and Maria Pateraki and Harry Coppock and Ivan Kiskin and Marianne Sinka and Stephen Roberts},
journal= {arXiv preprint arXiv:2205.06799},
year = {2022}
}
Comments
5 pages, part of the ACM Multimedia 2022 Grand Challenge "The ACM Multimedia 2022 Computational Paralinguistics Challenge (ComParE 2022)"