deep-music-genre-classification

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deep-music-genre-classification

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🎵 Using Deep Learning to Categorize Music as Time Progresses Through Spectrogram Analysis

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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](http://ijet.pl/index.php/ijet/article/view/10.2478-eletel-2014-0042/53), [Recommending music on Spotify with Deep Learning](http://benanne.github.io/2014/08/05/spotify-cnns.html), and [Convolutional-Recurrent Neural Network for Live Music Genre Recognition](http://deepsound.io/music_genre_recognition.html).

## 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](https://docs.google.com/presentation/d/1MANAML13S-PBGx8bsbI8gdaKGPJ2bPd_UNbA3E2txdg/edit?usp=sharing).

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