Dataset Open Access

The development dataset of the AI composition recognition competition, CSMT2020

Jing, Yinji; Li, Shengchen; Zhou, Wei; Zhu, Yidan; Li, Zijin; Fazekas, George; Zhang, Ru


DataCite XML Export

<?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">&lt;p&gt;The development dataset contains 6000 MIDI files with monophonic melodies generated by artificial intelligence algorithms. The tempo is between the 68bpm and&amp;nbsp;118bpm (beat per minute).&amp;nbsp;The length of each melody is 8 bars,&amp;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.&lt;/p&gt;

&lt;p&gt;The website of the challenge:&lt;/p&gt;

&lt;p&gt;&lt;a href="http://www.csmcw-csmt.cn/data/2020/ai-composition-recognition2020/"&gt;http://www.csmcw-csmt.cn/data/2020/ai-composition-recognition2020&lt;/a&gt;&amp;nbsp;(Chinese instruction)&lt;/p&gt;

&lt;p&gt;&lt;a href="https://ai-composition-recognition2020.github.io/english.html"&gt;https://ai-composition-recognition2020.github.io/english.html&lt;/a&gt;&amp;nbsp;(English instruction)&lt;/p&gt;</description>
  </descriptions>
</resource>
358
268
views
downloads
All versions This version
Views 358358
Downloads 268268
Data volume 645.9 MB645.9 MB
Unique views 273273
Unique downloads 160160

Share

Cite as