TY - CHAP A1 - Schuller, Björn A1 - Batliner, Anton A1 - Amiriparian, Shahin A1 - Bergler, Christian A1 - Gerczuk, Maurice A1 - Holz, Natalie A1 - Larrouy-Maestri, Pauline A1 - Bayerl, Sebastian P. A1 - Riedhammer, Korbinian A1 - Mallol-Ragolta, Adria A1 - Pateraki, Maria A1 - Coppock, Harry A1 - Kiskin, Ivan A1 - Sinka, Marianne A1 - Roberts, Stephen T1 - The ACM Multimedia 2022 Computational Paralinguistics Challenge BT - Vocalisations, Stuttering, Activity, & Mosquitoes N2 - 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. Y1 - 2022 U6 - https://doi.org/10.1145/3503161.3551591 ER -