Automatic Classification of Musical Instrument Samples

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Název: Automatic Classification of Musical Instrument Samples
Autoři: Daniele Scarano
Informace o vydavateli: Zenodo
Rok vydání: 2016
Sbírka: Zenodo
Témata: machine learning, signal processing, Freesound, content based classification
Popis: Automatic classification of musical instrument is an old research topic in music information retrieval. In this work we address the problem of the classification using musical instrument single note samples from Freesound and we put the accent on the content analysis of the sound and how those content information are connected to the physical characteristics of each instrument. We build a taxonomy based on instrument families and mode of excitation. The musical instruments play a central role in this work and the studies on timbre are used as a methodological base to apply feature selection to our complete set of descriptors, the aim of this is to find which descriptors are relevant to describe a specific instrument. The machine learning then is used as an instrument to evaluate our choices, to identify weakness and problem in the current implementation of audio descriptors.
Druh dokumentu: text
Jazyk: English
Relation: https://zenodo.org/communities/smc-master/; https://zenodo.org/records/3786212; oai:zenodo.org:3786212; https://doi.org/10.5281/zenodo.3786212
DOI: 10.5281/zenodo.3786212
Dostupnost: https://doi.org/10.5281/zenodo.3786212
https://zenodo.org/records/3786212
Rights: Creative Commons Attribution 4.0 International ; cc-by-4.0 ; https://creativecommons.org/licenses/by/4.0/legalcode
Přístupové číslo: edsbas.BDD3BA2E
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  – Url: https://doi.org/10.5281/zenodo.3786212#
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  Data: Automatic Classification of Musical Instrument Samples
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  Data: <searchLink fieldCode="AR" term="%22Daniele+Scarano%22">Daniele Scarano</searchLink>
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  Data: 2016
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  Data: Automatic classification of musical instrument is an old research topic in music information retrieval. In this work we address the problem of the classification using musical instrument single note samples from Freesound and we put the accent on the content analysis of the sound and how those content information are connected to the physical characteristics of each instrument. We build a taxonomy based on instrument families and mode of excitation. The musical instruments play a central role in this work and the studies on timbre are used as a methodological base to apply feature selection to our complete set of descriptors, the aim of this is to find which descriptors are relevant to describe a specific instrument. The machine learning then is used as an instrument to evaluate our choices, to identify weakness and problem in the current implementation of audio descriptors.
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      – SubjectFull: signal processing
        Type: general
      – SubjectFull: Freesound
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      – TitleFull: Automatic Classification of Musical Instrument Samples
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