Audio Onset Detection: A Brief History and Current Techniques

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IV.

REFERENCES

Agrawal, Y., Ravi Shanker, R. G. and Alluri, V. (2021) ‘Transformer-based Approach Towards Music Emotion Recognition from Lyrics’. Bello, J. P. et al. (2005) ‘A tutorial on onset detection in music signals’, 13(5), pp. 1035–1047. doi: 10.1109/TSA.2005.851998. Böck, S., Krebs, F. and Schedl, M. (2012) ‘Evaluating the Online Capabilities of Onset Detection Methods’. ISMIR. doi: 10.5281/zenodo.1416035. Böck, S. and Widmer, G. (2013) ‘Maximum Filter Vibrato Suppression for Onset Detection’. Dixon, S. (2006a) ‘Onset Detection Revisited’. Dixon, S. (2006b) ‘Simple Spectrum-Based Onset Detection’. Eck, D. and Lacoste, A. (2007) ‘A Supervised Classification Algorithm for Note Onset Detection’. Eck, D. and Schmidhuber, J. (2002) ‘Finding temporal structure in music: blues improvisation with LSTM recurrent networks’, in. IEEE (Proceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing), pp. 747–756. doi: 10.1109/NNSP.2002.1030094. Eyben, F. et al. (2010) ‘Universal Onset Detection with Bidirectional Long-Short Term Memory Neural Networks’. (11th International Society for Music Information Retrieval Conference). Available at: https://explore.openaire.eu/search/publication?articleId=od_______518::efb4c46cd113df0d8d82e393 eed27bd4. Gao, R. . and Yan, R. (2006) ‘Non-stationary signal processing for bearing health monitoring’, 1(1). doi: 10.1504/IJMR.2006.010701. Gong, R. and Serra, X. (2018) ‘Towards an efficient deep learning model for musical onset detection’. Available at: https://arxiv.org/abs/1806.06773. Lindqvist, B. (2019) Reproducing the State of the Art in Onset Detection Using Neural Networks. KTH, Skolan för elektroteknik och datavetenskap (EECS). Available at: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-255267. Marolt, M. and Kavčič, A. (2003) ‘Neural Networks for Note Onset Detection in Piano Music ’. Mottaghi, A. et al. (2017) ‘OBTAIN: Real-Time Beat Tracking in Audio Signals’, 5(4). doi: 10.18178/ijsps.5.4.123-129. Müller, M. (2016) Fundamentals of Music Processing : Audio, Analysis, Algorithms, Applications. Springer International Publishing, pp. 303–310. Available at: https://library.biblioboard.com/viewer/0f4841da-d67b-4a2a-822f-6fa532cef1b3. Park, Jonggwon et al. (2019) ‘A Bi-directional Transformer for Musical Chord Recognition’. Available at: https://arxiv.org/abs/1907.02698. Phi, M. (2018) Illustrated Guide to Recurrent Neural Networks. (Towards Data Science). Available at: https://towardsdatascience.com/illustrated-guide-to-recurrent-neural-networks-79e5eb8049c9 (Accessed: 2021).


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