Analysis of time-frequency representations for musical onset detection with convolutional neural network.
Bartłomiej Stasiak, Jędrzej Mońko
Citation: Proceedings of the 2016 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 8, pages 147–152 (2016)
Abstract. In this paper a convolutional neural network is applied to the problem of note onset detection in audio recordings. Two time-frequency representations are analysed, showing the superiority of standard spectrogram over enhanced autocorrelation (EAC) used as the input to the convolutional network. Experimental evaluation is based on a dataset containing 10,939 annotated onsets, with total duration of the audio recordings of over 45 min.
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