A Theory-Based Explainable Deep Learning Architecture for Music Emotion

This paper paper develops a theory-based, explainable deep learning convolutional neural network (CNN) classifier to predict the time-varying emotional response to music. We design novel CNN filters that leverage the frequency harmonics structure from acoustic physics known to impact the perception...

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Bibliographische Detailangaben

Hauptverfasser:	Fong, Hortense, Kumar, Vineet, Sudhir, K
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Artificial Intelligence Computer Science - Human-Computer Interaction Computer Science - Sound
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