Developing and testing sub-band spectral features in music genre and music mood machine learning

Developing and testing sub-band spectral features in music genre and music mood machine learning

Bibliographic Details
Main Author: Prezja, Fabi
Other Authors: Humanistis-yhteiskuntatieteellinen tiedekunta, Faculty of Humanities and Social Sciences, Musiikin, taiteen ja kulttuurin tutkimuksen laitos, Department of Music, Art and Culture Studies, Jyväskylän yliopisto, University of Jyväskylä, Music, Mind and Technology (maisteriohjelma), Master's Degree Programme in Music, Mind and Technology, 3054
Format: Master's thesis
Language:eng
Published: 2018
Subjects:
music information retrieval
music genre classification
music mood classification
sub-band features
polyphonic timbre
spectral features
adaptive spectral window decomposition
koneoppiminen
genret
luokitus (toiminta)
machine learning
genres
classification
Online Access: https://jyx.jyu.fi/handle/123456789/60963
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author Prezja, Fabi
author2 Humanistis-yhteiskuntatieteellinen tiedekunta Faculty of Humanities and Social Sciences Musiikin, taiteen ja kulttuurin tutkimuksen laitos Department of Music, Art and Culture Studies Jyväskylän yliopisto University of Jyväskylä Music, Mind and Technology (maisteriohjelma) Master's Degree Programme in Music, Mind and Technology 3054
author_facet Prezja, Fabi Humanistis-yhteiskuntatieteellinen tiedekunta Faculty of Humanities and Social Sciences Musiikin, taiteen ja kulttuurin tutkimuksen laitos Department of Music, Art and Culture Studies Jyväskylän yliopisto University of Jyväskylä Music, Mind and Technology (maisteriohjelma) Master's Degree Programme in Music, Mind and Technology 3054 Prezja, Fabi
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spellingShingle Prezja, Fabi Developing and testing sub-band spectral features in music genre and music mood machine learning music information retrieval music genre classification music mood classification sub-band features polyphonic timbre spectral features adaptive spectral window decomposition koneoppiminen genret luokitus (toiminta) machine learning genres classification
subject_txtF Music, Mind and Technology
thumbnail https://jyu.finna.fi/Cover/Show?source=Solr&id=jyx.123456789_60963&index=0&size=large
title Developing and testing sub-band spectral features in music genre and music mood machine learning
title_full Developing and testing sub-band spectral features in music genre and music mood machine learning
title_fullStr Developing and testing sub-band spectral features in music genre and music mood machine learning Developing and testing sub-band spectral features in music genre and music mood machine learning
title_full_unstemmed Developing and testing sub-band spectral features in music genre and music mood machine learning Developing and testing sub-band spectral features in music genre and music mood machine learning
title_short Developing and testing sub-band spectral features in music genre and music mood machine learning
title_sort developing and testing sub band spectral features in music genre and music mood machine learning
title_txtP Developing and testing sub-band spectral features in music genre and music mood machine learning
topic music information retrieval music genre classification music mood classification sub-band features polyphonic timbre spectral features adaptive spectral window decomposition koneoppiminen genret luokitus (toiminta) machine learning genres classification
topic_facet adaptive spectral window decomposition classification genres genret koneoppiminen luokitus (toiminta) machine learning music genre classification music information retrieval music mood classification polyphonic timbre spectral features sub-band features
url https://jyx.jyu.fi/handle/123456789/60963 http://www.urn.fi/URN:NBN:fi:jyu-201901081104
work_keys_str_mv AT prezjafabi developingandtestingsubbandspectralfeaturesinmusicgenreandmusicmoodmachinelearning

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