The ACM Multimedia 2022 Computational Paralinguistics Challenge: Vocalisations, Stuttering, Activity, & Mosquitoes
This work addresses specific challenges in paralinguistics and sensing for researchers, but it is incremental as it builds on existing competition frameworks and feature extraction techniques.
The paper tackled four computational paralinguistics problems—classifying human vocalizations and stuttering, recognizing human activity from smartwatch data, and detecting mosquitoes—by introducing new sub-challenges and baseline methods, achieving competitive results as part of a research competition.
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.