Guitar note onset detection based on a spectral sparsity measure. Mounir, M., Karsmakers, P., & van Waterschoot , T. In 2016 24th European Signal Processing Conference (EUSIPCO), pages 978-982, Aug, 2016.
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Paper doi abstract bibtex
Paper doi abstract bibtex The detection of note onsets is gaining a growing interest in audio signal processing research due to its wide range of applications in music information retrieval. We propose a new note onset detection algorithm NINOS2 exploiting the spectral sparsity difference between different parts of a musical note. When compared to the popular state-of-the-art LogFiltSpecFlux algorithm, the proposed algorithm shows up to 61% better performance for automatically annotated guitar melodies as well as chord progressions. We also propose an additional performance measure to assess the relative position of detected onsets w.r.t. each other.
@InProceedings{7760394,
author = {M. Mounir and P. Karsmakers and T. {van Waterschoot}},
booktitle = {2016 24th European Signal Processing Conference (EUSIPCO)},
title = {Guitar note onset detection based on a spectral sparsity measure},
year = {2016},
pages = {978-982},
abstract = {The detection of note onsets is gaining a growing interest in audio signal processing research due to its wide range of applications in music information retrieval. We propose a new note onset detection algorithm NINOS2 exploiting the spectral sparsity difference between different parts of a musical note. When compared to the popular state-of-the-art LogFiltSpecFlux algorithm, the proposed algorithm shows up to 61% better performance for automatically annotated guitar melodies as well as chord progressions. We also propose an additional performance measure to assess the relative position of detected onsets w.r.t. each other.},
keywords = {audio signal processing;information retrieval;music;musical instruments;guitar note onset detection;spectral sparsity measure;audio signal processing;music information retrieval;NINOS2;spectral sparsity difference;musical note;LogFiltSpecFlux algorithm;annotated guitar melodies;chord progressions;Music;Spectrogram;Transient analysis;Europe;Signal processing algorithms;Probabilistic logic},
doi = {10.1109/EUSIPCO.2016.7760394},
issn = {2076-1465},
month = {Aug},
url = {https://www.eurasip.org/proceedings/eusipco/eusipco2016/papers/1570256369.pdf},
}Downloads: 0
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