https://github.com/deezer/multi-view-ssl-benchmark
Repository for the ICASSP 2024 paper "An Experimental Comparison Of Multi-view Self-supervised Methods For Music Tagging".
https://github.com/deezer/multi-view-ssl-benchmark
audio-representation-learning icassp2024 music-information-retrieval music-tagging self-supervised-learning
Last synced: 9 months ago
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Repository for the ICASSP 2024 paper "An Experimental Comparison Of Multi-view Self-supervised Methods For Music Tagging".
- Host: GitHub
- URL: https://github.com/deezer/multi-view-ssl-benchmark
- Owner: deezer
- Created: 2024-01-11T13:47:24.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-05-20T07:43:40.000Z (over 1 year ago)
- Last Synced: 2025-02-10T18:14:54.582Z (11 months ago)
- Topics: audio-representation-learning, icassp2024, music-information-retrieval, music-tagging, self-supervised-learning
- Language: Python
- Homepage:
- Size: 1.46 MB
- Stars: 6
- Watchers: 5
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# An Experimental Comparison Of Multi-view Self-supervised Methods For Music Tagging
by [Gabriel Meseguer-Brocal](https://www.linkedin.com/in/gabriel-meseguer-brocal-1032a42b), [Dorian Desblancs](https://www.linkedin.com/in/dorian-desblancs), and [Romain Hennequin](http://romain-hennequin.fr/En/index.html).
## About
This repository contains the models and losses used to generate our results. All trained, self-supervised model weights can be found in the [Releases](https://github.com/deezer/multi-view-ssl-benchmark/releases) section of this repository.
## Getting Started
In order to explore our repository, one can start with the following:
```bash
# Clone and enter repository
git clone https://github.com/deezer/multi-view-ssl-benchmark
cd multi-view-ssl-benchmark
# Install dependencies
pip install poetry
poetry install
# Download sample audio example
wget https://github.com/deezer/multi-view-ssl-benchmark/releases/download/v0.0.1/weights.zip
unzip weights.zip
```
Sample code for model weight loading, audio loading, and embedding computation can then be found in `usage/sample.py`! Use the following command to run it:
```bash
poetry run python -m usage.sample
```
## Other
We also include the processing of two downstream tasks in `downstream_tasks/`, the `jamendo` and `mtat`. We unfortunately cannot do the same for the Million Song Dataset since it is mapped to songs in the Deezer catalogue.
## Reference
If you use this repository, please consider citing:
```
@inproceedings{meseguer2024experimental,
title={An Experimental Comparison of Multi-View Self-Supervised Methods for Music Tagging},
author={Meseguer-Brocal, Gabriel and Desblancs, Dorian and Hennequin, Romain},
booktitle={ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
pages={1141--1145},
year={2024},
organization={IEEE}
}
```
Our paper can be found on [arXiv](https://arxiv.org/abs/2404.09177) 🌟 The poster we presented at ICASSP 2024 can be found in this repo 🗄️