Music Technology Group
Specialized in audio signal processing, music information retrieval, musical interfaces, and computational musicology
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Essentia
Open-source library and AI models for audio and music analysis
Discover Essentia Industrial applicationsCall for participation in MediaEval 2020’s Emotion and Theme Recognition Task
The Benchmarking Initiative for Multimedia Evaluation (MediaEval) organizes an annual cycle of scientific evaluation tasks in the area of multimedia access and retrieval. This year the MTG is once again organising a task inviting participants to try their skills at automatically recognizing moods and themes conveyed by the audio tracks.
The task is framed as an auto-tagging problem with tags specific to moods and themes (e.g., happy, dark, epic, melodic, love, film, space). The task uses the MTG-Jamendo dataset presented at the Machine Learning for Music Discovery workshop at ICML 2019. A full description of the task is available here: https://multimediaeval.
All interested researchers are warmly welcomed to participate. Participants will be able to present their results at the MediaEval Multimedia Benchmark Workshop, to be held online in early December: https://
The task is organized by Music Technology Group, Universitat Pompeu Fabra (Dmitry Bogdanov, Alastair Porter, Philip Tovstogan, and Minz Won)
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