Automatic music transcription for traditional woodwind instruments sopele

•Prospects of sopele woodwind instrument AMT are inspected on a newly acquired dataset.•Unwanted pitch variation is mitigated using DFT and supervised machine learning.•DFT-coupled RF and CNN models achieve F1=0.92 in the polyphonic setup.•A full-stack system for effortless music preservation of sop...

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Veröffentlicht in:	Pattern recognition letters Jg. 128; S. 340 - 347
Hauptverfasser:	Skoki, Arian, Ljubic, Sandi, Lerga, Jonatan, Štajduhar, Ivan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 01.12.2019 Elsevier Science Ltd
Schlagworte:	Algorithms Applications programs Automatic music transcription Cultural heritage Cultural resources Discrete Fourier transform Feature extraction Frequency Learning algorithms Machine learning Mobile computing Model accuracy Musical scores Piercing Pitch Problem solving Singing Sopele Traditional woodwind instrument Transcription Woodwind music Sopele Traditional woodwind instrument Automatic music transcription Discrete Fourier transform Machine learning
ISSN:	0167-8655, 1872-7344
Online-Zugang:	Volltext
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