A data model for music information retrieval
Identifieur interne :
000123 ( PascalFrancis/Corpus );
précédent :
000122;
suivant :
000124
A data model for music information retrieval
Auteurs : Tamar BermanSource :
-
Lecture notes in computer science [ 0302-9743 ] ; 2006.
RBID : Pascal:07-0534512
Descripteurs français
- Pascal (Inist)
- Système information,
Recherche information,
Série temporelle,
Découverte connaissance,
Analyse donnée,
Extraction information,
Fouille donnée,
Interrogation base donnée,
Acoustique audio,
Acoustique musicale,
Tonie,
Musique,
Comportement utilisateur,
SQL,
Modèle donnée,
Modélisation,
Extraction forme,
Harmonique,
Temps occupation,
Intervalle temps,
..
English descriptors
- KwdEn :
- Audio acoustics,
Data analysis,
Data mining,
Data models,
Database query,
Harmonic,
Information extraction,
Information retrieval,
Information system,
Knowledge discovery,
Modeling,
Music,
Musical acoustics,
Occupation time,
Pattern extraction,
Pitch(acoustics),
SQL,
Time interval,
Time series,
User behavior.
Abstract
This paper describes a data model for the representation of tonal music. In this model, music is conceived as an equally-spaced time series of 12-dimensional vectors. The model has been successfully applied to the task of discovering frequently recurring patterns, and to the related task of retrieving user-defined musical patterns. This was accomplished by converting midi sequences of music by W.A. Mozart into the time series representation and analyzing these with data mining tools and SQL queries. The novelty of the pattern extraction capability supported by the model is in the potentially complex description of the sequences, which may contain both melodic and harmonic features, may be embedded within each other, or interspersed with other patterns or occurrences. A unique feature of the model is the use of time intervals as the basic representational unit, which fosters possibilities for future application to audio data.
Notice en format standard (ISO 2709)
Pour connaître la documentation sur le format Inist Standard.
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| A08 | 01 | 1 | ENG | @1 A data model for music information retrieval |
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| A09 | 01 | 1 | ENG | @1 Next generation information technologies and systems : 6th international conference, NGITS 2006, Kibbutz Shefayim, Israel, July 4-6, 2006 : proceedings |
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| A11 | 01 | 1 | | @1 BERMAN (Tamar) |
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| A12 | 01 | 1 | | @1 ETZION (Opher) @9 ed. |
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| A12 | 02 | 1 | | @1 KUFLIK (Tsvi) @9 ed. |
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| A12 | 03 | 1 | | @1 MOTRO (Amihai) @9 ed. |
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| A14 | 01 | | | @1 Graduate School of Library and Information Science University of Illinois at Urbana-Champaign @2 Champaign, IL 61820 @3 USA @Z 1 aut. |
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| A20 | | | | @1 165-173 |
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| A21 | | | | @1 2006 |
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| A23 | 01 | | | @0 ENG |
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| A26 | 01 | | | @0 3-540-35472-7 |
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| A43 | 01 | | | @1 INIST @2 16343 @5 354000153620160150 |
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| A44 | | | | @0 0000 @1 © 2007 INIST-CNRS. All rights reserved. |
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| A45 | | | | @0 15 ref. |
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| A47 | 01 | 1 | | @0 07-0534512 |
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| A60 | | | | @1 P @2 C |
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| A64 | 01 | 1 | | @0 Lecture notes in computer science |
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| A66 | 01 | | | @0 DEU |
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| C01 | 01 | | ENG | @0 This paper describes a data model for the representation of tonal music. In this model, music is conceived as an equally-spaced time series of 12-dimensional vectors. The model has been successfully applied to the task of discovering frequently recurring patterns, and to the related task of retrieving user-defined musical patterns. This was accomplished by converting midi sequences of music by W.A. Mozart into the time series representation and analyzing these with data mining tools and SQL queries. The novelty of the pattern extraction capability supported by the model is in the potentially complex description of the sequences, which may contain both melodic and harmonic features, may be embedded within each other, or interspersed with other patterns or occurrences. A unique feature of the model is the use of time intervals as the basic representational unit, which fosters possibilities for future application to audio data. |
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| C03 | 02 | X | SPA | @0 Búsqueda información @5 06 |
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| C03 | 03 | X | FRE | @0 Série temporelle @5 07 |
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| C03 | 03 | X | ENG | @0 Time series @5 07 |
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| C03 | 03 | X | SPA | @0 Serie temporal @5 07 |
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| C03 | 04 | X | SPA | @0 Descubrimiento conocimiento @5 08 |
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| C03 | 09 | 3 | ENG | @0 Audio acoustics @5 13 |
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| C03 | 10 | X | FRE | @0 Acoustique musicale @5 18 |
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| C03 | 10 | X | ENG | @0 Musical acoustics @5 18 |
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| C03 | 10 | X | SPA | @0 Acústica musical @5 18 |
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| C03 | 17 | X | FRE | @0 Extraction forme @5 25 |
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| C03 | 17 | X | ENG | @0 Pattern extraction @5 25 |
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| C03 | 17 | X | SPA | @0 Extracción forma @5 25 |
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| C03 | 18 | X | FRE | @0 Harmonique @5 26 |
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| C03 | 18 | X | ENG | @0 Harmonic @5 26 |
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| C03 | 18 | X | SPA | @0 Armónica @5 26 |
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| C03 | 19 | X | FRE | @0 Temps occupation @5 27 |
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| C03 | 19 | X | ENG | @0 Occupation time @5 27 |
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| C03 | 19 | X | SPA | @0 Tiempo ocupación @5 27 |
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| C03 | 20 | X | FRE | @0 Intervalle temps @5 28 |
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| C03 | 20 | X | ENG | @0 Time interval @5 28 |
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| C03 | 20 | X | SPA | @0 Intervalo tiempo @5 28 |
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| C03 | 21 | X | FRE | @0 . @4 INC @5 82 |
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| N21 | | | | @1 344 |
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| N44 | 01 | | | @1 OTO |
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| N82 | | | | @1 OTO |
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| pR |
| A30 | 01 | 1 | ENG | @1 NGITS 2006 @2 6 @3 Shefayim ISR @4 2006 |
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Format Inist (serveur)
| NO : | PASCAL 07-0534512 INIST |
|---|
| ET : | A data model for music information retrieval |
|---|
| AU : | BERMAN (Tamar); ETZION (Opher); KUFLIK (Tsvi); MOTRO (Amihai) |
|---|
| AF : | Graduate School of Library and Information Science University of Illinois at Urbana-Champaign/Champaign, IL 61820/Etats-Unis (1 aut.) |
|---|
| DT : | Publication en série; Congrès; Niveau analytique |
|---|
| SO : | Lecture notes in computer science; ISSN 0302-9743; Allemagne; Da. 2006; Vol. 4032; Pp. 165-173; Bibl. 15 ref. |
|---|
| LA : | Anglais |
|---|
| EA : | This paper describes a data model for the representation of tonal music. In this model, music is conceived as an equally-spaced time series of 12-dimensional vectors. The model has been successfully applied to the task of discovering frequently recurring patterns, and to the related task of retrieving user-defined musical patterns. This was accomplished by converting midi sequences of music by W.A. Mozart into the time series representation and analyzing these with data mining tools and SQL queries. The novelty of the pattern extraction capability supported by the model is in the potentially complex description of the sequences, which may contain both melodic and harmonic features, may be embedded within each other, or interspersed with other patterns or occurrences. A unique feature of the model is the use of time intervals as the basic representational unit, which fosters possibilities for future application to audio data. |
|---|
| CC : | 001D02B07D; 001D02B07B; 001B40C38 |
|---|
| FD : | Système information; Recherche information; Série temporelle; Découverte connaissance; Analyse donnée; Extraction information; Fouille donnée; Interrogation base donnée; Acoustique audio; Acoustique musicale; Tonie; Musique; Comportement utilisateur; SQL; Modèle donnée; Modélisation; Extraction forme; Harmonique; Temps occupation; Intervalle temps; . |
|---|
| ED : | Information system; Information retrieval; Time series; Knowledge discovery; Data analysis; Information extraction; Data mining; Database query; Audio acoustics; Musical acoustics; Pitch(acoustics); Music; User behavior; SQL; Data models; Modeling; Pattern extraction; Harmonic; Occupation time; Time interval |
|---|
| SD : | Sistema información; Búsqueda información; Serie temporal; Descubrimiento conocimiento; Análisis datos; Extracción información; Busca dato; Interrogación base datos; Acústica musical; Altura sonida; Música; Comportamiento usuario; Modelización; Extracción forma; Armónica; Tiempo ocupación; Intervalo tiempo |
|---|
| LO : | INIST-16343.354000153620160150 |
|---|
| ID : | 07-0534512 |
|---|
Links to Exploration step
Pascal:07-0534512
Le document en format XML
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</keywords><front><div type="abstract" xml:lang="en">This paper describes a data model for the representation of tonal music. In this model, music is conceived as an equally-spaced time series of 12-dimensional vectors. The model has been successfully applied to the task of discovering frequently recurring patterns, and to the related task of retrieving user-defined musical patterns. This was accomplished by converting midi sequences of music by W.A. Mozart into the time series representation and analyzing these with data mining tools and SQL queries. The novelty of the pattern extraction capability supported by the model is in the potentially complex description of the sequences, which may contain both melodic and harmonic features, may be embedded within each other, or interspersed with other patterns or occurrences. A unique feature of the model is the use of time intervals as the basic representational unit, which fosters possibilities for future application to audio data.</div>
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<s9>ed.</s9>
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<s5>20</s5>
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<s5>20</s5>
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<s5>21</s5>
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<s5>21</s5>
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<s5>21</s5>
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<s5>22</s5>
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<s5>22</s5>
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<s5>23</s5>
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<s5>23</s5>
</fC03><fC03 i1="16" i2="X" l="FRE"><s0>Modélisation</s0>
<s5>24</s5>
</fC03><fC03 i1="16" i2="X" l="ENG"><s0>Modeling</s0>
<s5>24</s5>
</fC03><fC03 i1="16" i2="X" l="SPA"><s0>Modelización</s0>
<s5>24</s5>
</fC03><fC03 i1="17" i2="X" l="FRE"><s0>Extraction forme</s0>
<s5>25</s5>
</fC03><fC03 i1="17" i2="X" l="ENG"><s0>Pattern extraction</s0>
<s5>25</s5>
</fC03><fC03 i1="17" i2="X" l="SPA"><s0>Extracción forma</s0>
<s5>25</s5>
</fC03><fC03 i1="18" i2="X" l="FRE"><s0>Harmonique</s0>
<s5>26</s5>
</fC03><fC03 i1="18" i2="X" l="ENG"><s0>Harmonic</s0>
<s5>26</s5>
</fC03><fC03 i1="18" i2="X" l="SPA"><s0>Armónica</s0>
<s5>26</s5>
</fC03><fC03 i1="19" i2="X" l="FRE"><s0>Temps occupation</s0>
<s5>27</s5>
</fC03><fC03 i1="19" i2="X" l="ENG"><s0>Occupation time</s0>
<s5>27</s5>
</fC03><fC03 i1="19" i2="X" l="SPA"><s0>Tiempo ocupación</s0>
<s5>27</s5>
</fC03><fC03 i1="20" i2="X" l="FRE"><s0>Intervalle temps</s0>
<s5>28</s5>
</fC03><fC03 i1="20" i2="X" l="ENG"><s0>Time interval</s0>
<s5>28</s5>
</fC03><fC03 i1="20" i2="X" l="SPA"><s0>Intervalo tiempo</s0>
<s5>28</s5>
</fC03><fC03 i1="21" i2="X" l="FRE"><s0>.</s0>
<s4>INC</s4>
<s5>82</s5>
</fC03><fN21><s1>344</s1>
</fN21><fN44 i1="01"><s1>OTO</s1>
</fN44><fN82><s1>OTO</s1>
</fN82><pR><fA30 i1="01" i2="1" l="ENG"><s1>NGITS 2006</s1>
<s2>6</s2>
<s3>Shefayim ISR</s3>
<s4>2006</s4>
</fA30><server><NO>PASCAL 07-0534512 INIST</NO>
<ET>A data model for music information retrieval</ET>
<AU>BERMAN (Tamar); ETZION (Opher); KUFLIK (Tsvi); MOTRO (Amihai)</AU>
<AF>Graduate School of Library and Information Science University of Illinois at Urbana-Champaign/Champaign, IL 61820/Etats-Unis (1 aut.)</AF>
<DT>Publication en série; Congrès; Niveau analytique</DT>
<SO>Lecture notes in computer science; ISSN 0302-9743; Allemagne; Da. 2006; Vol. 4032; Pp. 165-173; Bibl. 15 ref.</SO>
<LA>Anglais</LA>
<EA>This paper describes a data model for the representation of tonal music. In this model, music is conceived as an equally-spaced time series of 12-dimensional vectors. The model has been successfully applied to the task of discovering frequently recurring patterns, and to the related task of retrieving user-defined musical patterns. This was accomplished by converting midi sequences of music by W.A. Mozart into the time series representation and analyzing these with data mining tools and SQL queries. The novelty of the pattern extraction capability supported by the model is in the potentially complex description of the sequences, which may contain both melodic and harmonic features, may be embedded within each other, or interspersed with other patterns or occurrences. A unique feature of the model is the use of time intervals as the basic representational unit, which fosters possibilities for future application to audio data.</EA>
<CC>001D02B07D; 001D02B07B; 001B40C38</CC>
<FD>Système information; Recherche information; Série temporelle; Découverte connaissance; Analyse donnée; Extraction information; Fouille donnée; Interrogation base donnée; Acoustique audio; Acoustique musicale; Tonie; Musique; Comportement utilisateur; SQL; Modèle donnée; Modélisation; Extraction forme; Harmonique; Temps occupation; Intervalle temps; .</FD>
<ED>Information system; Information retrieval; Time series; Knowledge discovery; Data analysis; Information extraction; Data mining; Database query; Audio acoustics; Musical acoustics; Pitch(acoustics); Music; User behavior; SQL; Data models; Modeling; Pattern extraction; Harmonic; Occupation time; Time interval</ED>
<SD>Sistema información; Búsqueda información; Serie temporal; Descubrimiento conocimiento; Análisis datos; Extracción información; Busca dato; Interrogación base datos; Acústica musical; Altura sonida; Música; Comportamiento usuario; Modelización; Extracción forma; Armónica; Tiempo ocupación; Intervalo tiempo</SD>
<LO>INIST-16343.354000153620160150</LO>
<ID>07-0534512</ID>
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