Unsupervised Music Structure Annotation by Time Series Structure Features and Segment Similarity : Music Data Mining
Identifieur interne : 000099 ( Main/Exploration ); précédent : 000098; suivant : 000100Unsupervised Music Structure Annotation by Time Series Structure Features and Segment Similarity : Music Data Mining
Auteurs : Joan Serra [Espagne] ; Meinard Müller [Allemagne] ; Peter Grosche [Allemagne] ; Josep Ll. Arcos [Espagne]Source :
- IEEE transactions on multimedia [ 1520-9210 ] ; 2014.
Descripteurs français
- Pascal (Inist)
- Multimédia, Recherche information, Similitude, Annotation, Présentation document, Délai d'exécution, Réalité terrain, Acoustique musicale, Série temporelle, Solution similitude, Système hiérarchisé, Méthode globale locale, Musique, Etude expérimentale, Acoustique audio, Apprentissage non supervisé, Recherche par contenu.
- Wicri :
- topic : Multimédia, Musique.
English descriptors
- KwdEn :
Abstract
Automatically inferring the structural properties of raw multimedia documents is essential in today's digitized society. Given its hierarchical and multi-faceted organization, musical pieces represent a challenge for current computational systems. In this article, we present a novel approach to music structure annotation based on the combination of structure features with time series similarity. Structure features encapsulate both local and global properties of a time series, and allow us to detect boundaries between homogeneous, novel, or repeated segments. Time series similarity is used to identify equivalent segments, corresponding to musically meaningful parts. Extensive tests with a total of five benchmark music collections and seven different human annotations show that the proposed approach is robust to different ground truth choices and parameter settings. Moreover, we see that it outperforms previous approaches evaluated under the same framework.
Affiliations:
- Allemagne, Espagne
- Bavière, Catalogne, District de Moyenne-Franconie, Sarre (Land)
- Erlangen, Sarrebruck
Links toward previous steps (curation, corpus...)
- to stream PascalFrancis, to step Corpus: 000002
- to stream PascalFrancis, to step Curation: 000011
- to stream PascalFrancis, to step Checkpoint: 000000
- to stream Main, to step Merge: 000099
- to stream Main, to step Curation: 000099
Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en" level="a">Unsupervised Music Structure Annotation by Time Series Structure Features and Segment Similarity : Music Data Mining</title>
<author><name sortKey="Serra, Joan" sort="Serra, Joan" uniqKey="Serra J" first="Joan" last="Serra">Joan Serra</name>
<affiliation wicri:level="2"><inist:fA14 i1="01"><s1>IIIA-CSIC, Campus de la UAB s/n</s1>
<s2>08193 Bellaterra</s2>
<s3>ESP</s3>
<sZ>1 aut.</sZ>
<sZ>4 aut.</sZ>
</inist:fA14>
<country>Espagne</country>
<placeName><region nuts="2" type="communauté">Catalogne</region>
</placeName>
</affiliation>
</author>
<author><name sortKey="Muller, Meinard" sort="Muller, Meinard" uniqKey="Muller M" first="Meinard" last="Müller">Meinard Müller</name>
<affiliation wicri:level="1"><inist:fA14 i1="02"><s1>International Audio Laboratories Erlangen</s1>
<s2>91058 Erlangen</s2>
<s3>DEU</s3>
<sZ>2 aut.</sZ>
</inist:fA14>
<country>Allemagne</country>
<wicri:noRegion>91058 Erlangen</wicri:noRegion>
<placeName><settlement type="city">Erlangen</settlement>
<region type="land" nuts="1">Bavière</region>
<region type="district" nuts="2">District de Moyenne-Franconie</region>
</placeName>
</affiliation>
</author>
<author><name sortKey="Grosche, Peter" sort="Grosche, Peter" uniqKey="Grosche P" first="Peter" last="Grosche">Peter Grosche</name>
<affiliation wicri:level="3"><inist:fA14 i1="03"><s1>Saarland University and the Max-Planck Institut für Informatik, Campus E1.4</s1>
<s2>66123 Saarbrücken</s2>
<s3>DEU</s3>
<sZ>3 aut.</sZ>
</inist:fA14>
<country>Allemagne</country>
<placeName><region type="land" nuts="2">Sarre (Land)</region>
<settlement type="city">Sarrebruck</settlement>
</placeName>
</affiliation>
</author>
<author><name sortKey="Arcos, Josep Ll" sort="Arcos, Josep Ll" uniqKey="Arcos J" first="Josep Ll." last="Arcos">Josep Ll. Arcos</name>
<affiliation wicri:level="2"><inist:fA14 i1="01"><s1>IIIA-CSIC, Campus de la UAB s/n</s1>
<s2>08193 Bellaterra</s2>
<s3>ESP</s3>
<sZ>1 aut.</sZ>
<sZ>4 aut.</sZ>
</inist:fA14>
<country>Espagne</country>
<placeName><region nuts="2" type="communauté">Catalogne</region>
</placeName>
</affiliation>
</author>
</titleStmt>
<publicationStmt><idno type="wicri:source">INIST</idno>
<idno type="inist">14-0220601</idno>
<date when="2014">2014</date>
<idno type="stanalyst">PASCAL 14-0220601 INIST</idno>
<idno type="RBID">Pascal:14-0220601</idno>
<idno type="wicri:Area/PascalFrancis/Corpus">000002</idno>
<idno type="wicri:Area/PascalFrancis/Curation">000011</idno>
<idno type="wicri:Area/PascalFrancis/Checkpoint">000000</idno>
<idno type="wicri:explorRef" wicri:stream="PascalFrancis" wicri:step="Checkpoint">000000</idno>
<idno type="wicri:doubleKey">1520-9210:2014:Serra J:unsupervised:music:structure</idno>
<idno type="wicri:Area/Main/Merge">000099</idno>
<idno type="wicri:Area/Main/Curation">000099</idno>
<idno type="wicri:Area/Main/Exploration">000099</idno>
</publicationStmt>
<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a">Unsupervised Music Structure Annotation by Time Series Structure Features and Segment Similarity : Music Data Mining</title>
<author><name sortKey="Serra, Joan" sort="Serra, Joan" uniqKey="Serra J" first="Joan" last="Serra">Joan Serra</name>
<affiliation wicri:level="2"><inist:fA14 i1="01"><s1>IIIA-CSIC, Campus de la UAB s/n</s1>
<s2>08193 Bellaterra</s2>
<s3>ESP</s3>
<sZ>1 aut.</sZ>
<sZ>4 aut.</sZ>
</inist:fA14>
<country>Espagne</country>
<placeName><region nuts="2" type="communauté">Catalogne</region>
</placeName>
</affiliation>
</author>
<author><name sortKey="Muller, Meinard" sort="Muller, Meinard" uniqKey="Muller M" first="Meinard" last="Müller">Meinard Müller</name>
<affiliation wicri:level="1"><inist:fA14 i1="02"><s1>International Audio Laboratories Erlangen</s1>
<s2>91058 Erlangen</s2>
<s3>DEU</s3>
<sZ>2 aut.</sZ>
</inist:fA14>
<country>Allemagne</country>
<wicri:noRegion>91058 Erlangen</wicri:noRegion>
<placeName><settlement type="city">Erlangen</settlement>
<region type="land" nuts="1">Bavière</region>
<region type="district" nuts="2">District de Moyenne-Franconie</region>
</placeName>
</affiliation>
</author>
<author><name sortKey="Grosche, Peter" sort="Grosche, Peter" uniqKey="Grosche P" first="Peter" last="Grosche">Peter Grosche</name>
<affiliation wicri:level="3"><inist:fA14 i1="03"><s1>Saarland University and the Max-Planck Institut für Informatik, Campus E1.4</s1>
<s2>66123 Saarbrücken</s2>
<s3>DEU</s3>
<sZ>3 aut.</sZ>
</inist:fA14>
<country>Allemagne</country>
<placeName><region type="land" nuts="2">Sarre (Land)</region>
<settlement type="city">Sarrebruck</settlement>
</placeName>
</affiliation>
</author>
<author><name sortKey="Arcos, Josep Ll" sort="Arcos, Josep Ll" uniqKey="Arcos J" first="Josep Ll." last="Arcos">Josep Ll. Arcos</name>
<affiliation wicri:level="2"><inist:fA14 i1="01"><s1>IIIA-CSIC, Campus de la UAB s/n</s1>
<s2>08193 Bellaterra</s2>
<s3>ESP</s3>
<sZ>1 aut.</sZ>
<sZ>4 aut.</sZ>
</inist:fA14>
<country>Espagne</country>
<placeName><region nuts="2" type="communauté">Catalogne</region>
</placeName>
</affiliation>
</author>
</analytic>
<series><title level="j" type="main">IEEE transactions on multimedia</title>
<title level="j" type="abbreviated">IEEE trans. multimedia</title>
<idno type="ISSN">1520-9210</idno>
<imprint><date when="2014">2014</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
<seriesStmt><title level="j" type="main">IEEE transactions on multimedia</title>
<title level="j" type="abbreviated">IEEE trans. multimedia</title>
<idno type="ISSN">1520-9210</idno>
</seriesStmt>
</fileDesc>
<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Annotation</term>
<term>Audio acoustics</term>
<term>Content-based retrieval</term>
<term>Document layout</term>
<term>Experimental study</term>
<term>Global local method</term>
<term>Ground truth</term>
<term>Hierarchical system</term>
<term>Information retrieval</term>
<term>Multimedia</term>
<term>Music</term>
<term>Musical acoustics</term>
<term>Similarity</term>
<term>Similarity solution</term>
<term>Time allowed</term>
<term>Time series</term>
<term>Unsupervised learning</term>
</keywords>
<keywords scheme="Pascal" xml:lang="fr"><term>Multimédia</term>
<term>Recherche information</term>
<term>Similitude</term>
<term>Annotation</term>
<term>Présentation document</term>
<term>Délai d'exécution</term>
<term>Réalité terrain</term>
<term>Acoustique musicale</term>
<term>Série temporelle</term>
<term>Solution similitude</term>
<term>Système hiérarchisé</term>
<term>Méthode globale locale</term>
<term>Musique</term>
<term>Etude expérimentale</term>
<term>Acoustique audio</term>
<term>Apprentissage non supervisé</term>
<term>Recherche par contenu</term>
</keywords>
<keywords scheme="Wicri" type="topic" xml:lang="fr"><term>Multimédia</term>
<term>Musique</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en">Automatically inferring the structural properties of raw multimedia documents is essential in today's digitized society. Given its hierarchical and multi-faceted organization, musical pieces represent a challenge for current computational systems. In this article, we present a novel approach to music structure annotation based on the combination of structure features with time series similarity. Structure features encapsulate both local and global properties of a time series, and allow us to detect boundaries between homogeneous, novel, or repeated segments. Time series similarity is used to identify equivalent segments, corresponding to musically meaningful parts. Extensive tests with a total of five benchmark music collections and seven different human annotations show that the proposed approach is robust to different ground truth choices and parameter settings. Moreover, we see that it outperforms previous approaches evaluated under the same framework.</div>
</front>
</TEI>
<affiliations><list><country><li>Allemagne</li>
<li>Espagne</li>
</country>
<region><li>Bavière</li>
<li>Catalogne</li>
<li>District de Moyenne-Franconie</li>
<li>Sarre (Land)</li>
</region>
<settlement><li>Erlangen</li>
<li>Sarrebruck</li>
</settlement>
</list>
<tree><country name="Espagne"><region name="Catalogne"><name sortKey="Serra, Joan" sort="Serra, Joan" uniqKey="Serra J" first="Joan" last="Serra">Joan Serra</name>
</region>
<name sortKey="Arcos, Josep Ll" sort="Arcos, Josep Ll" uniqKey="Arcos J" first="Josep Ll." last="Arcos">Josep Ll. Arcos</name>
</country>
<country name="Allemagne"><region name="Bavière"><name sortKey="Muller, Meinard" sort="Muller, Meinard" uniqKey="Muller M" first="Meinard" last="Müller">Meinard Müller</name>
</region>
<name sortKey="Grosche, Peter" sort="Grosche, Peter" uniqKey="Grosche P" first="Peter" last="Grosche">Peter Grosche</name>
</country>
</tree>
</affiliations>
</record>
Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Wicri/Sarre/explor/MusicSarreV3/Data/Main/Exploration
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000099 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd -nk 000099 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien |wiki= Wicri/Sarre |area= MusicSarreV3 |flux= Main |étape= Exploration |type= RBID |clé= Pascal:14-0220601 |texte= Unsupervised Music Structure Annotation by Time Series Structure Features and Segment Similarity : Music Data Mining }}
This area was generated with Dilib version V0.6.33. |