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Recent advances in deep learning accelerated the development of content-based automatic music tagging systems.
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K. Choi, G. Fazekas, M. Sandler, and K. Cho, “Convolutional recurrent neural networks for music classification,” in Proc. of International Conference on Acoustics, Speech and Signal Processing (ICASSP) . IEEE, 2017, pp. 2392–2396
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J. Pons, O. Nieto, M. Prockup, E. Schmidt, A. Ehmann, and X. Serra, “End-to-end learning for music audio tagging at scale,” In Proc. of the 19th International Society for Music Information Retrieval Conference (ISMIR) , 2018
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T. Kim, J. Lee, and J. Nam, “Sample-level cnn architectures for music auto-tagging using raw waveforms,” in Proc. of International Conference on Acoustics, Speech and Signal Processing (ICASSP) . IEEE, 2018, pp. 366–370
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2019
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D. Bogdanov, M. Won, P. Tovstogan, A. Porter, and X. Serra, “The mtg-jamendo dataset for automatic music tagging,” Machine Learning for Music Discovery Workshop, International Conference on Machine Learning (ICML) , 2019
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M. Won, S. Chun, , O. Nieto, and X. Serra, “Data-driven harmonic filters for audio representation learning,” In Proc. of International Conference on Acoustics, Speech and Signal Processing (ICASSP) , 2020
2020
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