Music pattern mining for chromosome representation in evolutionary composition

Artificial intelligence (AI) has bloomed in many novel fields such as computational creativity. Recently, research on automatic composition using AI technology, especially evolutionary algorithms, has received considerable promising results. Traditionally, chromosomes are represented as a series of...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Chien-Hung Liu, Chuan-Kang Ting
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	automatic composition Biological cells creative intelligence Data mining Evolutionary computation genetic algorithm Genetic algorithms Genetics Music pattern mining Sociology
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

container_end_page	2152
container_issue
container_start_page	2145
container_title
container_volume
creator	Chien-Hung Liu Chuan-Kang Ting
description	Artificial intelligence (AI) has bloomed in many novel fields such as computational creativity. Recently, research on automatic composition using AI technology, especially evolutionary algorithms, has received considerable promising results. Traditionally, chromosomes are represented as a series of numbers to indicate the notes for evolutionary composition. This study attempts to explore the composition styles by mining music patterns of a specific composer. The patterns are used as genes for chromosome representation. Accordingly, the composition styles are considered in generating music by evolutionary algorithms. The fitness function is based on music theory to smooth the progression between phrases. Experimental results show that the patterns mined from compositions can reflect the composer's style and benefit generating satisfactory songs by evolutionary algorithms.
doi_str_mv	10.1109/CEC.2015.7257149
format	Conference Proceeding
fullrecord	<record><control><sourceid>ieee_RIE</sourceid><recordid>TN_cdi_ieee_primary_7257149</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>7257149</ieee_id><sourcerecordid>7257149</sourcerecordid><originalsourceid>FETCH-LOGICAL-i123t-ce8dcaa69fd2c041337157ac1ae53187c642b2c5dbadd34129093b24f06dd213</originalsourceid><addsrcrecordid>eNotkMtOwzAURA0CibawR2LjH0jx9SOOlygqD6nApgt2lWPfgFFjR3aKxN_Tiq5mzuZoNITcAlsCMHPfrtolZ6CWmisN0pyROUhtjJaG63MyAyOhYozXF4fOGlNp3XxckXkp34yBVGBm5O11X4Kjo50mzJEOIYb4SfuUqfvKaUglDUgzjhkLxslOIUUaIsWftNsfweZf6tIwphKOeE0ue7sreHPKBdk8rjbtc7V-f3ppH9ZVAC6mymHjnbW16T13TIIQGpS2DiwqAY12teQdd8p31nshgRtmRMdlz2rvOYgFufvXBkTcjjkMhx3b0w3iD7ePURs</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Music pattern mining for chromosome representation in evolutionary composition</title><source>IEEE Electronic Library (IEL)</source><creator>Chien-Hung Liu ; Chuan-Kang Ting</creator><creatorcontrib>Chien-Hung Liu ; Chuan-Kang Ting</creatorcontrib><description>Artificial intelligence (AI) has bloomed in many novel fields such as computational creativity. Recently, research on automatic composition using AI technology, especially evolutionary algorithms, has received considerable promising results. Traditionally, chromosomes are represented as a series of numbers to indicate the notes for evolutionary composition. This study attempts to explore the composition styles by mining music patterns of a specific composer. The patterns are used as genes for chromosome representation. Accordingly, the composition styles are considered in generating music by evolutionary algorithms. The fitness function is based on music theory to smooth the progression between phrases. Experimental results show that the patterns mined from compositions can reflect the composer's style and benefit generating satisfactory songs by evolutionary algorithms.</description><identifier>ISSN: 1089-778X</identifier><identifier>EISSN: 1941-0026</identifier><identifier>EISBN: 1479974927</identifier><identifier>EISBN: 9781479974924</identifier><identifier>DOI: 10.1109/CEC.2015.7257149</identifier><language>eng</language><publisher>IEEE</publisher><subject>automatic composition ; Biological cells ; creative intelligence ; Data mining ; Evolutionary computation ; genetic algorithm ; Genetic algorithms ; Genetics ; Music ; pattern mining ; Sociology</subject><ispartof>2015 IEEE Congress on Evolutionary Computation (CEC), 2015, p.2145-2152</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/7257149$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,792,23909,23910,25118,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/7257149$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Chien-Hung Liu</creatorcontrib><creatorcontrib>Chuan-Kang Ting</creatorcontrib><title>Music pattern mining for chromosome representation in evolutionary composition</title><title>2015 IEEE Congress on Evolutionary Computation (CEC)</title><addtitle>CEC</addtitle><description>Artificial intelligence (AI) has bloomed in many novel fields such as computational creativity. Recently, research on automatic composition using AI technology, especially evolutionary algorithms, has received considerable promising results. Traditionally, chromosomes are represented as a series of numbers to indicate the notes for evolutionary composition. This study attempts to explore the composition styles by mining music patterns of a specific composer. The patterns are used as genes for chromosome representation. Accordingly, the composition styles are considered in generating music by evolutionary algorithms. The fitness function is based on music theory to smooth the progression between phrases. Experimental results show that the patterns mined from compositions can reflect the composer's style and benefit generating satisfactory songs by evolutionary algorithms.</description><subject>automatic composition</subject><subject>Biological cells</subject><subject>creative intelligence</subject><subject>Data mining</subject><subject>Evolutionary computation</subject><subject>genetic algorithm</subject><subject>Genetic algorithms</subject><subject>Genetics</subject><subject>Music</subject><subject>pattern mining</subject><subject>Sociology</subject><issn>1089-778X</issn><issn>1941-0026</issn><isbn>1479974927</isbn><isbn>9781479974924</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2015</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotkMtOwzAURA0CibawR2LjH0jx9SOOlygqD6nApgt2lWPfgFFjR3aKxN_Tiq5mzuZoNITcAlsCMHPfrtolZ6CWmisN0pyROUhtjJaG63MyAyOhYozXF4fOGlNp3XxckXkp34yBVGBm5O11X4Kjo50mzJEOIYb4SfuUqfvKaUglDUgzjhkLxslOIUUaIsWftNsfweZf6tIwphKOeE0ue7sreHPKBdk8rjbtc7V-f3ppH9ZVAC6mymHjnbW16T13TIIQGpS2DiwqAY12teQdd8p31nshgRtmRMdlz2rvOYgFufvXBkTcjjkMhx3b0w3iD7ePURs</recordid><startdate>20150501</startdate><enddate>20150501</enddate><creator>Chien-Hung Liu</creator><creator>Chuan-Kang Ting</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>20150501</creationdate><title>Music pattern mining for chromosome representation in evolutionary composition</title><author>Chien-Hung Liu ; Chuan-Kang Ting</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i123t-ce8dcaa69fd2c041337157ac1ae53187c642b2c5dbadd34129093b24f06dd213</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2015</creationdate><topic>automatic composition</topic><topic>Biological cells</topic><topic>creative intelligence</topic><topic>Data mining</topic><topic>Evolutionary computation</topic><topic>genetic algorithm</topic><topic>Genetic algorithms</topic><topic>Genetics</topic><topic>Music</topic><topic>pattern mining</topic><topic>Sociology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chien-Hung Liu</creatorcontrib><creatorcontrib>Chuan-Kang Ting</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>Chien-Hung Liu</au><au>Chuan-Kang Ting</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Music pattern mining for chromosome representation in evolutionary composition</atitle><btitle>2015 IEEE Congress on Evolutionary Computation (CEC)</btitle><stitle>CEC</stitle><date>2015-05-01</date><risdate>2015</risdate><spage>2145</spage><epage>2152</epage><pages>2145-2152</pages><issn>1089-778X</issn><eissn>1941-0026</eissn><eisbn>1479974927</eisbn><eisbn>9781479974924</eisbn><abstract>Artificial intelligence (AI) has bloomed in many novel fields such as computational creativity. Recently, research on automatic composition using AI technology, especially evolutionary algorithms, has received considerable promising results. Traditionally, chromosomes are represented as a series of numbers to indicate the notes for evolutionary composition. This study attempts to explore the composition styles by mining music patterns of a specific composer. The patterns are used as genes for chromosome representation. Accordingly, the composition styles are considered in generating music by evolutionary algorithms. The fitness function is based on music theory to smooth the progression between phrases. Experimental results show that the patterns mined from compositions can reflect the composer's style and benefit generating satisfactory songs by evolutionary algorithms.</abstract><pub>IEEE</pub><doi>10.1109/CEC.2015.7257149</doi><tpages>8</tpages></addata></record>
fulltext	fulltext_linktorsrc
identifier	ISSN: 1089-778X
ispartof	2015 IEEE Congress on Evolutionary Computation (CEC), 2015, p.2145-2152
issn	1089-778X 1941-0026
language	eng
recordid	cdi_ieee_primary_7257149
source	IEEE Electronic Library (IEL)
subjects	automatic composition Biological cells creative intelligence Data mining Evolutionary computation genetic algorithm Genetic algorithms Genetics Music pattern mining Sociology
title	Music pattern mining for chromosome representation in evolutionary composition
url	https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-05T05%3A05%3A38IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Music%20pattern%20mining%20for%20chromosome%20representation%20in%20evolutionary%20composition&rft.btitle=2015%20IEEE%20Congress%20on%20Evolutionary%20Computation%20(CEC)&rft.au=Chien-Hung%20Liu&rft.date=2015-05-01&rft.spage=2145&rft.epage=2152&rft.pages=2145-2152&rft.issn=1089-778X&rft.eissn=1941-0026&rft_id=info:doi/10.1109/CEC.2015.7257149&rft_dat=%3Cieee_RIE%3E7257149%3C/ieee_RIE%3E%3Curl%3E%3C/url%3E&rft.eisbn=1479974927&rft.eisbn_list=9781479974924&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=7257149&rfr_iscdi=true