References
[1]. E. Benetos, S. Dixon, Z. Duan, and S. Ewert, “Automatic music transcription: An overview,” IEEE Signal Processing Magazine, vol. 36, no. 1, pp. 20–30, 2018.
[2]. B. Bhattarai and J. Lee, “A comprehensive review on music transcription,” Applied Sciences, vol. 13, no. 21, p. 11882, 2023.
[3]. A. Krizhevsky, I. Sutskever, and G. E. Hinton, “Imagenet classification with deep convolutional neural networks,” Advances in neural information processing systems, vol. 25, 2012.
[4]. C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich, “Going deeper with convolutions,” in Proceedings of the IEEE conference on computer vision and pattern recognition, 2015, pp. 1–9.
[5]. K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” in Proceedings of the IEEE conference on computer vision and pattern recognition, 2016, pp. 770–778.
[6]. Y. Yan, F. Cwitkowitz, and Z. Duan, “Skipping the frame-level: Event-based piano transcription with neural semi-crfs,” Advances in Neural Information Processing Systems, vol. 34, pp. 20583–20595, 2021.
[7]. Y. Yan and Z. Duan, “Scoring intervals using non-hierarchical transformer for automatic piano transcription,” arXiv preprint arXiv:2404.09466, 2024.
[8]. C. Hawthorne, E. Elsen, J. Song, A. Roberts, I. Simon, C. Raffel, J. Engel, S. Oore, and D. Eck, “Onsets and frames: Dual-objective piano transcription,” arXiv preprint arXiv:1710.11153, 2017.
[9]. Q. Kong, B. Li, X. Song, Y. Wan, and Y. Wang, “High-resolution piano transcription with pedals by regressing onset and offset times,” IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 29, pp. 3707–3717, 2021.
[10]. T. Kwon, D. Jeong, and J. Nam, “Polyphonic piano transcription using autoregressive multi-state note model,” arXiv preprint arXiv:2010.01104, 2020.
[11]. R. Kelz, S. Bock, and G. Widmer, “Deep polyphonic adsr piano note transcription,” in¨ ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2019, pp. 246–250.
[12]. A. Vaswani, “Attention is all you need,” Advances in Neural Information Processing Systems, 2017.
[13]. S. Sarawagi and W. W. Cohen, “Semi-markov conditional random fields for information extraction,” Advances in neural information processing systems, vol. 17, 2004.
Cite this article
Hao,S. (2024). Transformer-based Note level Automatic Drum-Set Transcription. Applied and Computational Engineering,113,52-56.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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References
[1]. E. Benetos, S. Dixon, Z. Duan, and S. Ewert, “Automatic music transcription: An overview,” IEEE Signal Processing Magazine, vol. 36, no. 1, pp. 20–30, 2018.
[2]. B. Bhattarai and J. Lee, “A comprehensive review on music transcription,” Applied Sciences, vol. 13, no. 21, p. 11882, 2023.
[3]. A. Krizhevsky, I. Sutskever, and G. E. Hinton, “Imagenet classification with deep convolutional neural networks,” Advances in neural information processing systems, vol. 25, 2012.
[4]. C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich, “Going deeper with convolutions,” in Proceedings of the IEEE conference on computer vision and pattern recognition, 2015, pp. 1–9.
[5]. K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” in Proceedings of the IEEE conference on computer vision and pattern recognition, 2016, pp. 770–778.
[6]. Y. Yan, F. Cwitkowitz, and Z. Duan, “Skipping the frame-level: Event-based piano transcription with neural semi-crfs,” Advances in Neural Information Processing Systems, vol. 34, pp. 20583–20595, 2021.
[7]. Y. Yan and Z. Duan, “Scoring intervals using non-hierarchical transformer for automatic piano transcription,” arXiv preprint arXiv:2404.09466, 2024.
[8]. C. Hawthorne, E. Elsen, J. Song, A. Roberts, I. Simon, C. Raffel, J. Engel, S. Oore, and D. Eck, “Onsets and frames: Dual-objective piano transcription,” arXiv preprint arXiv:1710.11153, 2017.
[9]. Q. Kong, B. Li, X. Song, Y. Wan, and Y. Wang, “High-resolution piano transcription with pedals by regressing onset and offset times,” IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 29, pp. 3707–3717, 2021.
[10]. T. Kwon, D. Jeong, and J. Nam, “Polyphonic piano transcription using autoregressive multi-state note model,” arXiv preprint arXiv:2010.01104, 2020.
[11]. R. Kelz, S. Bock, and G. Widmer, “Deep polyphonic adsr piano note transcription,” in¨ ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2019, pp. 246–250.
[12]. A. Vaswani, “Attention is all you need,” Advances in Neural Information Processing Systems, 2017.
[13]. S. Sarawagi and W. W. Cohen, “Semi-markov conditional random fields for information extraction,” Advances in neural information processing systems, vol. 17, 2004.