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pro vyhledávání: '"Adrien Ycart"'
Publikováno v:
Transactions of the International Society for Music Information Retrieval, Vol 3, Iss 1 (2020)
Automatic Music Transcription (AMT) is usually evaluated using low-level criteria, typically by counting the number of errors, with equal weighting. Yet, some errors (e.g. out-of-key notes) are more salient than others. In this study, we design an on
Externí odkaz:
https://doaj.org/article/31ba7b541ef14e04a23cd6eb1ac5c818
Autor:
Emmanouil Benetos, Adrien Ycart
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing. 28:1328-1341
Music language models play an important role for various music signal and symbolic music processing tasks, such as music generation, symbolic music classification, or automatic music transcription (AMT). In this article, we investigate Long Short-Ter
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::241c0260bfa6969aa6bf0430d8aadd1c
https://doi.org/10.1109/taslp.2020.2987130
https://doi.org/10.1109/taslp.2020.2987130
Autor:
Emmanouil Benetos, Adrien Ycart
Publikováno v:
ICASSP
Automatic transcription of polyphonic music remains a challenging task in the field of Music Information Retrieval. In this paper, we propose a new method to post-process the output of a multi-pitch detection model using recurrent neural networks. In
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4eacc42c63084d6ba54ea73fd69125c2
https://doi.org/10.1109/icassp.2018.8462128
https://doi.org/10.1109/icassp.2018.8462128