Extracting significant repeating figures in music by using quantized melody contour
To extract music features from the raw data of music object and organize them as the music indices is important for music retrieval. A repeating pattern is a series of notes which appear more than once. Most of the repeating patterns are themes or tones for people to remember easily. A figure is def...
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creator | Chuan-Wang Chang Jiau, H.C. |
description | To extract music features from the raw data of music object and organize them as the music indices is important for music retrieval. A repeating pattern is a series of notes which appear more than once. Most of the repeating patterns are themes or tones for people to remember easily. A figure is defined as a melody contour of a musical segment. A sequence pattern is a melody segment that has the same figure with other melody segments. In this paper, we use the idea of interval between two adjacent notes to form quantized melody contour for representing music objects. This representation differs from existing methods that use notes to form a melody string. We also propose a method to find significant repeating figures. These figures could cover most of the repeating patterns that are in a noted melody string. In addition, the number of repeating figures found in samples of music is less than that of repeating patterns. As a result, the total execution time and memory space can be dramatically decreased. |
doi_str_mv | 10.1109/ISCC.2003.1214255 |
format | Conference Proceeding |
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A repeating pattern is a series of notes which appear more than once. Most of the repeating patterns are themes or tones for people to remember easily. A figure is defined as a melody contour of a musical segment. A sequence pattern is a melody segment that has the same figure with other melody segments. In this paper, we use the idea of interval between two adjacent notes to form quantized melody contour for representing music objects. This representation differs from existing methods that use notes to form a melody string. We also propose a method to find significant repeating figures. These figures could cover most of the repeating patterns that are in a noted melody string. In addition, the number of repeating figures found in samples of music is less than that of repeating patterns. As a result, the total execution time and memory space can be dramatically decreased.</description><identifier>ISSN: 1530-1346</identifier><identifier>ISBN: 9780769519616</identifier><identifier>ISBN: 076951961X</identifier><identifier>EISSN: 2642-7389</identifier><identifier>DOI: 10.1109/ISCC.2003.1214255</identifier><language>eng</language><publisher>IEEE</publisher><subject>Cities and towns ; Content based retrieval ; Data mining ; Feature extraction ; Microphones ; Multimedia databases ; Multiple signal classification ; Music information retrieval ; Query processing ; Research and development</subject><ispartof>Proceedings of the Eighth IEEE Symposium on Computers and Communications. 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As a result, the total execution time and memory space can be dramatically decreased.</description><subject>Cities and towns</subject><subject>Content based retrieval</subject><subject>Data mining</subject><subject>Feature extraction</subject><subject>Microphones</subject><subject>Multimedia databases</subject><subject>Multiple signal classification</subject><subject>Music information retrieval</subject><subject>Query processing</subject><subject>Research and development</subject><issn>1530-1346</issn><issn>2642-7389</issn><isbn>9780769519616</isbn><isbn>076951961X</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2003</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotkM1KxDAUhYM_YB3nAcRNXqA1N2nS3qWUUQcGXIyuh_Q2KZFpO_YHrE9v0Vl9cM7HWRzG7kEkAAIft_uiSKQQKgEJqdT6gkXSpDLOVI6XbI1ZLjKDGtCAuWIRaCViUKm5YbfD8CmEyLXMIrbffI-9pTG0NR9C3QYfyLYj793J2b_Uh3rq3cBDy5tpCMTLmS9cmq9pMcOPq3jjjl01c-rasZv6O3bt7XFw6zNX7ON58168xru3l23xtIsDZHqMSSE5IFAKSmOo8pkRKtUaLeaqdLqSpMnnQIZyaTxaIouoSsRSpH5xV-zhfzc45w6nPjS2nw_nP9Qvd7ZTjA</recordid><startdate>2003</startdate><enddate>2003</enddate><creator>Chuan-Wang Chang</creator><creator>Jiau, H.C.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>2003</creationdate><title>Extracting significant repeating figures in music by using quantized melody contour</title><author>Chuan-Wang Chang ; Jiau, H.C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-c39ce1c1331b66cdf76034559a983be5d2c5cf81c6c826f9acca993b99b04f603</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2003</creationdate><topic>Cities and towns</topic><topic>Content based retrieval</topic><topic>Data mining</topic><topic>Feature extraction</topic><topic>Microphones</topic><topic>Multimedia databases</topic><topic>Multiple signal classification</topic><topic>Music information retrieval</topic><topic>Query processing</topic><topic>Research and development</topic><toplevel>online_resources</toplevel><creatorcontrib>Chuan-Wang Chang</creatorcontrib><creatorcontrib>Jiau, H.C.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Chuan-Wang Chang</au><au>Jiau, H.C.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Extracting significant repeating figures in music by using quantized melody contour</atitle><btitle>Proceedings of the Eighth IEEE Symposium on Computers and Communications. ISCC 2003</btitle><stitle>ISCC</stitle><date>2003</date><risdate>2003</risdate><spage>1061</spage><epage>1066 vol.2</epage><pages>1061-1066 vol.2</pages><issn>1530-1346</issn><eissn>2642-7389</eissn><isbn>9780769519616</isbn><isbn>076951961X</isbn><abstract>To extract music features from the raw data of music object and organize them as the music indices is important for music retrieval. A repeating pattern is a series of notes which appear more than once. Most of the repeating patterns are themes or tones for people to remember easily. A figure is defined as a melody contour of a musical segment. A sequence pattern is a melody segment that has the same figure with other melody segments. In this paper, we use the idea of interval between two adjacent notes to form quantized melody contour for representing music objects. This representation differs from existing methods that use notes to form a melody string. We also propose a method to find significant repeating figures. These figures could cover most of the repeating patterns that are in a noted melody string. In addition, the number of repeating figures found in samples of music is less than that of repeating patterns. As a result, the total execution time and memory space can be dramatically decreased.</abstract><pub>IEEE</pub><doi>10.1109/ISCC.2003.1214255</doi></addata></record> |
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subjects | Cities and towns Content based retrieval Data mining Feature extraction Microphones Multimedia databases Multiple signal classification Music information retrieval Query processing Research and development |
title | Extracting significant repeating figures in music by using quantized melody contour |
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