Music Auto-Tagging
12 papers with code • 4 benchmarks • 3 datasets
Benchmarks
These leaderboards are used to track progress in Music Auto-Tagging
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MagnaTagATune
Latest papers with no code
Music Auto-Tagging with Robust Music Representation Learned via Domain Adversarial Training
Music auto-tagging is crucial for enhancing music discovery and recommendation.
WikiMuTe: A web-sourced dataset of semantic descriptions for music audio
The model is evaluated on two tasks: tag-based music retrieval and music auto-tagging.
Metric Learning vs Classification for Disentangled Music Representation Learning
For this, we (1) outline past work on the relationship between metric learning and classification, (2) extend this relationship to multi-label data by exploring three different learning approaches and their disentangled versions, and (3) evaluate all models on four tasks (training time, similarity retrieval, auto-tagging, and triplet prediction).
How Low Can You Go? Reducing Frequency and Time Resolution in Current CNN Architectures for Music Auto-tagging
Automatic tagging of music is an important research topic in Music Information Retrieval and audio analysis algorithms proposed for this task have achieved improvements with advances in deep learning.
Audio-based Distributional Semantic Models for Music Auto-tagging and Similarity Measurement
The recent development of Audio-based Distributional Semantic Models (ADSMs) enables the computation of audio and lexical vector representations in a joint acoustic-semantic space.
