Music Classification
21 papers with code • 0 benchmarks • 8 datasets
Benchmarks
These leaderboards are used to track progress in Music Classification
Libraries
Use these libraries to find Music Classification models and implementationsDatasets
MagnaTagATune
EMOPIA
JS Fake Chorales
Most implemented papers
Receptive-Field Regularized CNNs for Music Classification and Tagging
However, the MIR field is still dominated by the classical VGG-based CNN architecture variants, often in combination with more complex modules such as attention, and/or techniques such as pre-training on large datasets.
Contrastive Learning of Musical Representations
spijkervet/CLMR
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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.
Exploring modality-agnostic representations for music classification
We train music instrument classifiers that can take both images or sounds as input, and perform comparably to sound-only or image-only classifiers.
BERT-like Pre-training for Symbolic Piano Music Classification Tasks
This article presents a benchmark study of symbolic piano music classification using the masked language modelling approach of the Bidirectional Encoder Representations from Transformers (BERT).
Music Classification: Beyond Supervised Learning, Towards Real-world Applications
music-classification/tutorial
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The target audience for this web book is researchers and practitioners who are interested in state-of-the-art music classification research and building real-world applications.
S3T: Self-Supervised Pre-training with Swin Transformer for Music Classification
To our knowledge, S3T is the first method combining the Swin Transformer with a self-supervised learning method for music classification.
Low-Resource Music Genre Classification with Cross-Modal Neural Model Reprogramming
In this work, we introduce a novel method for leveraging pre-trained models for low-resource (music) classification based on the concept of Neural Model Reprogramming (NMR).
Symbolic Music Structure Analysis with Graph Representations and Changepoint Detection Methods
In the past, there have been several works that attempt to segment music into the audio and symbolic domains, however, the identification and segmentation of the music structure at different levels is still an open research problem in this area.
Audio Embeddings as Teachers for Music Classification
suncerock/EAsT-music-classification
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Music classification has been one of the most popular tasks in the field of music information retrieval.
MusicAgent: An AI Agent for Music Understanding and Generation with Large Language Models
microsoft/muzic
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For developers and amateurs, it is very difficult to grasp all of these task to satisfy their requirements in music processing, especially considering the huge differences in the representations of music data and the model applicability across platforms among various tasks.
