Open Access
| Issue |
ITM Web Conf.
Volume 84, 2026
2026 International Conference on Advent Trends in Computational Intelligence and Data Science (ATCIDS 2026)
|
|
|---|---|---|
| Article Number | 03025 | |
| Number of page(s) | 10 | |
| Section | Large Language Models, Generative AI, and Multimodal Learning | |
| DOI | https://doi.org/10.1051/itmconf/20268403025 | |
| Published online | 06 April 2026 | |
- A. Mehra, & P. Narang. Classification and study of music genres with multimodal Spectro-Lyrical Embeddings for Music (SLEM). Multimed Tools Appl 84, 3701–3721 (2025) [Google Scholar]
- G. Ru, X. Zhang, J. Wang, et al. Improving music genre classification from multi-modal properties of music and genre correlations perspective//ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2023: 1–5. (2023) [Google Scholar]
- T. F. Tavares and F. J. Ayres, Multi-label cross-lingual auto-matic music genre classification from lyrics with sentence bert, arXiv preprint arXiv:2501.03769 (2025) [Google Scholar]
- E. V. Epure, G. Salha-Galvan, & R. Hennequin. Multilingual Music Genre Embeddings for Effective Cross-Lingual Music Item Annotation. ArXiv, abs/2009.07755. (2020) [Google Scholar]
- M. Agrawal, A. Nandy. A novel multimodal music genre classifier using hierarchical attention and convolutional neural network. arXiv preprint arXiv:2011.11970. (2020) [Google Scholar]
- X. Favory, K. Drossos, T. Virtanen, et al. Learning contextual tag embeddings for cross-modal alignment of audio and tags//ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 596-600. (2021) [Google Scholar]
- I. Manco, E. Benetos, E. Quinton, et al. Contrastive audio-language learning for music. arXiv preprint arXiv:2208.12208. (2022) [Google Scholar]
- Q. Huang, A. Jansen, J. Lee, et al. Mulan: A joint embedding of music audio and natural language. arXiv preprint arXiv:2208.12415. (2022) [Google Scholar]
- A. Ferraro, X. Favory, K. Drossos, et al. Enriched music representations with multiple cross-modal contrastive learning. IEEE Signal Processing Letters, 28, 733–737. (2021) [Google Scholar]
- I. Manco, E. Benetos, E. Quinton, et al. Learning music audio representations via weak language supervision//ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 456-460. (2022) [Google Scholar]
- G. Tzanetakis, P. Cook. Musical genre classification of audio signals. IEEE Transactions on speech and audio processing, 10(5), 293–302. (2002) [Google Scholar]
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