The ACM Multimedia 2023 Computational Paralinguistics Challenge: Emotion Share & Requests
It addresses specific speech analysis tasks for the multimedia research community, but is incremental as it builds on existing challenges and methods.
The paper tackled two computational paralinguistics problems—emotion regression from speech and detection of requests/complaints—by establishing a research competition with baseline methods, achieving results through defined benchmarks.
The ACM Multimedia 2023 Computational Paralinguistics Challenge addresses two different problems for the first time in a research competition under well-defined conditions: In the Emotion Share Sub-Challenge, a regression on speech has to be made; and in the Requests Sub-Challenges, requests and complaints need to be detected. We describe the Sub-Challenges, baseline feature extraction, and classifiers based on the usual ComPaRE features, the auDeep toolkit, and deep feature extraction from pre-trained CNNs using the DeepSpectRum toolkit; in addition, wav2vec2 models are used.