@inproceedings{Schuller2022,

title = {The ACM Multimedia 2022 Computational Paralinguistics Challenge: Vocalisations, Stuttering, Activity, \& Mosquitoes},

author = {Bj\"{o}rn Schuller and Anton Batliner and Shahin Amiriparian and Christian Bergler and Maurice Gerczuk and Natalie Holz and Pauline Larrouy-Maestri and Sebastien Bayerl and Korbinian Riedhammer and Adria Mallol-Ragolta and Maria Pateraki and Harry Coppock and Ivan Kiskin and Marianne Sinka and Stephen Roberts},

url = {https://doi.org/10.1145/3503161.3551591},

doi = {10.1145/3503161.3551591},

isbn = {9781450392037},

year  = {2022},

date = {2022-10-10},

urldate = {2022-10-10},

booktitle = {Proceedings of the 30th ACM International Conference on Multimedia},

pages = {7120\textendash7124},

publisher = {Association for Computing Machinery},

address = {Lisboa, Portugal},

series = {MM '22},

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 = {Benchmark, Challenge, Computational Paralinguistics, Human Activity Recognition, Mosquito Detection, Stuttering, Vocalisations},

pubstate = {published},

tppubtype = {inproceedings}

}