Dataset Open Access
Jing, Yinji; Li, Shengchen; Zhou, Wei; Zhu, Yidan; Li, Zijin; Fazekas, George; Zhang, Ru
<?xml version='1.0' encoding='utf-8'?> <resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd"> <identifier identifierType="DOI">10.5281/zenodo.3944685</identifier> <creators> <creator> <creatorName>Jing, Yinji</creatorName> <givenName>Yinji</givenName> <familyName>Jing</familyName> <affiliation>Beijing University of Posts and Telecommunications</affiliation> </creator> <creator> <creatorName>Li, Shengchen</creatorName> <givenName>Shengchen</givenName> <familyName>Li</familyName> <affiliation>Beijing University of Posts and Telecommunications</affiliation> </creator> <creator> <creatorName>Zhou, Wei</creatorName> <givenName>Wei</givenName> <familyName>Zhou</familyName> <affiliation>Beijing Zhongwen Law Firm</affiliation> </creator> <creator> <creatorName>Zhu, Yidan</creatorName> <givenName>Yidan</givenName> <familyName>Zhu</familyName> <affiliation>Beijing Acoustics Society</affiliation> </creator> <creator> <creatorName>Li, Zijin</creatorName> <givenName>Zijin</givenName> <familyName>Li</familyName> <affiliation>China Conservatory of Music</affiliation> </creator> <creator> <creatorName>Fazekas, George</creatorName> <givenName>George</givenName> <familyName>Fazekas</familyName> <affiliation>Queen Mary University of London</affiliation> </creator> <creator> <creatorName>Zhang, Ru</creatorName> <givenName>Ru</givenName> <familyName>Zhang</familyName> <affiliation>Beijing University of Posts and Telecommunications</affiliation> </creator> </creators> <titles> <title>The development dataset of the AI composition recognition competition, CSMT2020</title> </titles> <publisher>Zenodo</publisher> <publicationYear>2020</publicationYear> <subjects> <subject>MIDI</subject> <subject>CSMT data challenge</subject> <subject>AI music composition</subject> </subjects> <dates> <date dateType="Issued">2020-07-15</date> </dates> <language>en</language> <resourceType resourceTypeGeneral="Dataset"/> <alternateIdentifiers> <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/3944685</alternateIdentifier> </alternateIdentifiers> <relatedIdentifiers> <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.3944684</relatedIdentifier> </relatedIdentifiers> <version>1.0</version> <rightsList> <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights> <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights> </rightsList> <descriptions> <description descriptionType="Abstract"><p>The development dataset contains 6000 MIDI files with monophonic melodies generated by artificial intelligence algorithms. The tempo is between the 68bpm and&nbsp;118bpm (beat per minute).&nbsp;The length of each melody is 8 bars,&nbsp;and the melody does not necessarily include complete phrase structures. There are two datasets with different music styles used as the training dataset of a certain number of algorithms, where the melodies in the development dataset are generated.</p> <p>The website of the challenge:</p> <p><a href="http://www.csmcw-csmt.cn/data/2020/ai-composition-recognition2020/">http://www.csmcw-csmt.cn/data/2020/ai-composition-recognition2020</a>&nbsp;(Chinese instruction)</p> <p><a href="https://ai-composition-recognition2020.github.io/english.html">https://ai-composition-recognition2020.github.io/english.html</a>&nbsp;(English instruction)</p></description> </descriptions> </resource>
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