mlsanityData to 14 Oct 2026

musicnn: Pre-trained convolutional neural networks for music audio tagging

arXiv 1909.06654 ↗First posted 14 Sep 2019cs.SD cs.CL eess.AScited by 50

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Abstract (arXiv)

Pronounced as "musician", the musicnn library contains a set of pre-trained musically motivated convolutional neural networks for music audio tagging: https://github.com/jordipons/musicnn. This repository also includes some pre-trained vgg-like baselines. These models can be used as out-of-the-box music audio taggers, as music feature extractors, or as pre-trained models for transfer learning. We also provide the code to train the aforementioned models: https://github.com/jordipons/musicnn-training. This framework also allows implementing novel models. For example, a musically motivated convolutional neural network with an attention-based output layer (instead of the temporal pooling layer) can achieve state-of-the-art results for music audio tagging: 90.77 ROC-AUC / 38.61 PR-AUC on the MagnaTagATune dataset --- and 88.81 ROC-AUC / 31.51 PR-AUC on the Million Song Dataset.

Key facts. Cited by 50 papers in the map (data through 14 Oct 2026). First posted on arXiv 14 Sep 2019.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 3; 2022: 12; 2023: 11; 2024: 12; 2025: 6; 2026: 6.

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  1. 2023MERT: Acoustic Music Understanding Model with Large-Scale Self-supervised Trainingcited by 181
  2. 2021Codified audio language modeling learns useful representations for music information retrievalcited by 64
  3. 2023MARBLE: Music Audio Representation Benchmark for Universal Evaluationcited by 38
  4. 2022Supervised and Unsupervised Learning of Audio Representations for Music Understandingcited by 35
  5. 2024Music2Latent: Consistency Autoencoders for Latent Audio Compressioncited by 33
  6. 2022MAP-Music2Vec: A Simple and Effective Baseline for Self-Supervised Music Audio Representation Learningcited by 22
  7. 2023MuseChat: A Conversational Music Recommendation System for Videoscited by 21
  8. 2022It's Time for Artistic Correspondence in Music and Videocited by 18
  9. 2023Language-Guided Music Recommendation for Video via Prompt Analogiescited by 18
  10. 2022Low-Resource Music Genre Classification with Cross-Modal Neural Model Reprogrammingcited by 17
  11. 2024A Multimodal Single-Branch Embedding Network for Recommendation in Cold-Start and Missing Modality Scenarioscited by 13
  12. 2022Flow Moods: Recommending Music by Moods on Deezercited by 11
38 more
  1. 2022Contrastive Learning with Positive-Negative Frame Mask for Music Representationcited by 10
  2. 2024ECC Analyzer: Extract Trading Signal from Earnings Conference Calls using Large Language Model for Stock Performance Predictioncited by 9
  3. 2024LC-Protonets: Multi-Label Few-Shot Learning for World Music Audio Taggingcited by 7
  4. 2022Jointist: Joint Learning for Multi-instrument Transcription and Its Applicationscited by 6
  5. 2024Music Foundation Model as Generic Booster for Music Downstream Taskscited by 6
  6. 2022Towards Proper Contrastive Self-supervised Learning Strategies For Music Audio Representationcited by 5
  7. 2023Learning Music Sequence Representation from Text Supervisioncited by 5
  8. 2023From West to East: Who can understand the music of the others better?cited by 5
  9. 2025FilmComposer: LLM-Driven Music Production for Silent Film Clipscited by 5
  10. 2022Exploiting Negative Preference in Content-based Music Recommendation with Contrastive Learningcited by 4
  11. 2025Music2Latent2: Audio Compression with Summary Embeddings and Autoregressive Decodingcited by 4
  12. 2025A Comprehensive Survey on Generative AI for Video-to-Music Generationcited by 4
  13. 2021Deep Learning Based EDM Subgenre Classification using Mel-Spectrogram and Tempogram Featurescited by 3
  14. 2022Learning Unsupervised Hierarchies of Audio Conceptscited by 3
  15. 2022Music Instrument Classification Reprogrammedcited by 3
  16. 2023Jointist: Simultaneous Improvement of Multi-instrument Transcription and Music Source Separation via Joint Trainingcited by 3
  17. 2025Myna: Masking-Based Contrastive Learning of Musical Representationscited by 3
  18. 2025Universal Music Representations? Evaluating Foundation Models on World Music Corporacited by 3
  19. 2024MVBIND: Self-Supervised Music Recommendation For Videos Via Embedding Space Bindingcited by 2
  20. 2024PIAST: A Multimodal Piano Dataset with Audio, Symbolic and Textcited by 2
  21. 2023What You Hear Is What You See: Audio Quality Metrics From Image Quality Metricscited by 1
  22. 2023Towards Contrastive Learning in Music Video Domaincited by 1
  23. 2023MDSC: Towards Evaluating the Style Consistency Between Music and Dancecited by 1
  24. 2023A Holistic Evaluation of Piano Sound Qualitycited by 1
  25. 2024A Computational Analysis of Lyric Similarity Perceptioncited by 1
  26. 2024Towards Training Music Taggers on Synthetic Datacited by 1
  27. 2024Music auto-tagging in the long tail: A few-shot approachcited by 1
  28. 2021Multi-task Learning with Metadata for Music Mood Classificationcited by 0
  29. 2022Pathway to Future Symbiotic Creativitycited by 0
  30. 2024An approach to hummed-tune and song sequences matchingcited by 0
  31. 2024Combining Genre Classification and Harmonic-Percussive Features with Diffusion Models for Music-Video Generationcited by 0
  32. 2025Learning Music Audio Representations With Limited Datacited by 0
  33. 2026Linear Complexity Self-Supervised Learning for Music Understanding with Random Quantizercited by 0
  34. 2026Scalable Music Cover Retrieval Using Lyrics-Aligned Audio Embeddingscited by 0
  35. 2026LabelBuddy: An Open Source Music and Audio Language Annotation Tagging Tool Using AI Assistancecited by 0
  36. 2026Constructing Composite Features for Interpretable Music-Taggingcited by 0
  37. 2026Multimodal Music Recommendation System using LLMscited by 0
  38. 2026Self-Representation Alignment in Diffusion Models for Video Background Music Generationcited by 0