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The online estimation of rhythmic information, such as beat positions, downbeat positions, and meter, is critical for many real-time music applications.
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T. Cheng, S. Fukayama, and M. Goto, “Joint beat and downbeat tracking based on CRNN models and a comparison of using different context ranges in convolutional layers,” in in Proc. of the International Computer Music Conference (ICMC) , 2016
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S.Böck, F. Krebs, and G.Widmer, “A multi-model approach to beat tracking considering heterogeneous music styles,” in In Proc. of the 15th Intl. Conf. on Music Information Retrieval (ISMIR) , 2014, pp. 603–608
2014
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J. L. Oliveira, F. Gouyon, L. G. Martins, , and L. P. Reis, “IBT: A real-time tempo and beat tracking system,” in In Proc. of the 11th Intl. Conf. on Music Information Retrieval (ISMIR) , 2014, pp. 291–296
2014
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A. Srinivasamurthy and X. Serra, “A supervised approach to hierarchical metrical cycle tracking from audio music recordings,” in In Proc. of the IEEE Int. Conference on Acoustics, Speech, and Signal Processing (ICASSP) , 2014
2014
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S. Durand, J. Bello, B. D., and G. Richard, “Downbeat tracking with multiple features and deep neural networks,” in In Proc. IEEE Int. Conf. Acoust. Speech Signal Process. (ICASSP) , 2015
2015
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F. Krebs, A. Holzapfel, A. T. Cemgil, and G. Widmer, “Inferring metrical structure in music using particle filters,” IEEE/ACM Transactions on audio, speech, and language processing , vol. 23, no. 5, pp. 111–222, May 2015
2015
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F. Krebs, S. Böck, and G. Widmer, “An efficient state-space model for joint tempo and meter tracking,” in In Proc. of the 16th Intl. Conf. on Music Information Retrieval (ISMIR) , 2015
2015
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U. Marchand and G. Peeters, “Swing ratio estimation,” in In Proc. of the 18th Int. Conference on Digital Audio Effects (DAFx) , 2015
2015
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S. Durand, J. P. Bello, B. D., and G. Richard, “Feature adapted convolutional neural networks for downbeat tracking,” in In Proc. IEEE Int. Conf. Acoust. Speech Signal Process. (ICASSP) , 2016
2016
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A. Mottaghi, K. Behdin, A. Esmaeili, M. Heydari, , and F. Marvasti, “OBTAIN: Real-time beat tracking in audio signals index terms—onset strength signal, tempo estimation, beat onset, cumulative beat strength signal, peak detection,” International Journal of Signal Processing Systems , pp. 123–129, 2017
2017
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S. Durand, J. P. Bello, B. David, , and G. Richard, “Robust downbeat tracking using an ensemble of convolutional networks,” Proceedings of the 17th International Society for Music Information Retrieval Conference, ISMIR 2016 , vol. 25, no. 1, pp. 255–261, 2017
2017
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S. Böck, F. Krebs, A. Durand, S. Pöll, and R. Balsyte, “ROBOD: a real-time online beat and offbeat drummer sebastian,” in 2017 IEEE signal processing cup , 2017
2017
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C.-Y. Liang, “Implementing and adapting a downbeat tracking system for real-time applications,” in Master Thesis , Carnegie Mellon University, 2017
2017
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M. Fuentes, B. Mcfee, H. C. Crayencour, S. Essid, and J. P. Bello, “Analysis of common design choices in deep learning systems for downbeat tracking,” in Proc. of the 19th Int. Society for Music Information Retrieval Conf. , 2018
2018
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M. E. P. Davies and S.Böck, “Temporal convolutional networks for musical audio beat tracking,” in In Proc. of the 27th European Signal Processing Conference (EUSIPCO) , 2019
2019
Later among the works it cites.
B. D. Giorgi, M. Mauch, , and M. Levy, “Downbeat tracking with tempo-invariant convolutional neural networks,” in In Proc. of the 17th Intl. Conf. on Music Information Retrieval (ISMIR) , 2020, pp. 216–222
2020
Later among the works it cites.
S. Böck and M. E. P. Davies, “Deconstruct, analyse, reconstruct: How to improve tempo, beat, and downbeat estimation,” in Proc. of the 21th Int. Society for Music Information Retrieval Conf. , 2020, pp. 574–582
2020
Later among the works it cites.
M. Heydari and Z. Duan, “Don’t look back: An online beat tracking method using RNN and enhanced particle filtering,” in In Proc. IEEE Int. Conf. Acoust. Speech Signal Process. (ICASSP) , 2021
2021
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