@inproceedings{SchullerBatlinerAmiriparianetal.2022, author = {Schuller, Bj{\"o}rn and Batliner, Anton and Amiriparian, Shahin and Bergler, Christian and Gerczuk, Maurice and Holz, Natalie and Larrouy-Maestri, Pauline and Bayerl, Sebastian P. and Riedhammer, Korbinian and Mallol-Ragolta, Adria and Pateraki, Maria and Coppock, Harry and Kiskin, Ivan and Sinka, Marianne and Roberts, Stephen}, title = {The ACM Multimedia 2022 Computational Paralinguistics Challenge}, doi = {10.1145/3503161.3551591}, pages = {7120-7124}, year = {2022}, 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.}, language = {en} }