Convolutional neural networks for music classification

E786388

"Convolutional neural networks for music classification" is a research work by Sander Dieleman that applies deep convolutional neural network architectures to automatically analyze and categorize music audio.

Try in SPARQL Jump to: Statements Referenced by

Statements (28)

Predicate Object
instanceOf music information retrieval research
research work
scientific paper
appliesTo music audio analysis
author Sander Dieleman NERFINISHED
comparesWith hand-crafted audio features
demonstrates effectiveness of deep convolutional architectures for music tasks
field audio signal processing
deep learning
machine learning
music information retrieval
focusesOn automatic genre classification
automatic music tagging
music classification
supervised learning
goal automatic analysis of music audio
automatic categorization of music audio
hasAuthor Sander Dieleman NERFINISHED
inputRepresentation spectrograms
time–frequency representations of audio
inputType music audio
language English
relatedTo audio content-based retrieval
automatic playlist generation
music recommendation systems
topic end-to-end learning for music classification
representation learning from raw or minimally processed audio
usesMethod convolutional neural networks

Referenced by (1)

Full triples — surface form annotated when it differs from this entity's canonical label.

Sander Dieleman notableWork Convolutional neural networks for music classification