Music Auto-Tagging
12 papers with code • 4 benchmarks • 3 datasets
Benchmarks
These leaderboards are used to track progress in Music Auto-Tagging
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
|||||
|
|||||
|
|||||
|
MagnaTagATune
Latest papers
Pre-training Music Classification Models via Music Source Separation
FaceOnLive/Spleeter-Android-iOS
•
•
In this paper, we study whether music source separation can be used as a pre-training strategy for music representation learning, targeted at music classification tasks.
Audio Embeddings as Teachers for Music Classification
suncerock/EAsT-music-classification
•
•
Music classification has been one of the most popular tasks in the field of music information retrieval.
Multi-Source Contrastive Learning from Musical Audio
Contrastive learning constitutes an emerging branch of self-supervised learning that leverages large amounts of unlabeled data, by learning a latent space, where pairs of different views of the same sample are associated.
Deep Learning Based EDM Subgenre Classification using Mel-Spectrogram and Tempogram Features
mir-aidj/edm-subgenre-classifier
•
•
Along with the evolution of music technology, a large number of styles, or "subgenres," of Electronic Dance Music(EDM) have emerged in recent years.
Contrastive Learning of Musical Representations
spijkervet/CLMR
•
•
A linear classifier trained on the proposed representations achieves a higher average precision than supervised models on the MagnaTagATune dataset, and performs comparably on the Million Song dataset.
TräumerAI: Dreaming Music with StyleGAN
The goal of this paper to generate a visually appealing video that responds to music with a neural network so that each frame of the video reflects the musical characteristics of the corresponding audio clip.
Evaluation of CNN-based Automatic Music Tagging Models
minzwon/sota-music-tagging-models
•
•
Recent advances in deep learning accelerated the development of content-based automatic music tagging systems.
Deep Content-User Embedding Model for Music Recommendation
jongpillee/deep-content-user
•
•
Recently deep learning based recommendation systems have been actively explored to solve the cold-start problem using a hybrid approach.
Sample-level CNN Architectures for Music Auto-tagging Using Raw Waveforms
tae-jun/resemul
•
•
Recent work has shown that the end-to-end approach using convolutional neural network (CNN) is effective in various types of machine learning tasks.
Sample-level Deep Convolutional Neural Networks for Music Auto-tagging Using Raw Waveforms
kyungyunlee/sampleCNN-pytorch
•
•
Recently, the end-to-end approach that learns hierarchical representations from raw data using deep convolutional neural networks has been successfully explored in the image, text and speech domains.
