evanotero / Deep Music Genre Classification
Licence: gpl-3.0
🎵 Using Deep Learning to Categorize Music as Time Progresses Through Spectrogram Analysis
Stars: ✭ 23
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Deep Music Genre Classification
Using deep learning to categorize music as time progresses through dpectrogram snalysis.
About
Our aim is to create a neural network (CNN + LSTM RNN) that recognizes music genre and provides a user-friendly visualization for the network's current belief of the genre of a song.
This project uses Keras, using TensorFlow for the backend, for the neural network and Tornado for serving requests.
Background
The rationale for this particular model is based on several works, primarily Grzegorz Gwardys and Daniel Grzywczak, Deep Image Features in Music Information Retrieval, Recommending music on Spotify with Deep Learning, and Convolutional-Recurrent Neural Network for Live Music Genre Recognition.
Data
Spectrogram Representation
TODO
Dataset
TODO
Model
Motivation
TODO
Architecture
TODO
Results
Summary Statistics
TODO
Conclusion
TODO
Demo
TODO
Usage
TODO
Slides
The slide deck can be found on Google Slides: Using Deep Learning to Categorize Music as Time Progresses Through Spectrogram Analysis.
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