July 15, 2020 Dataset Open Access

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

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    "description": "<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>\n\n<p>The website of the challenge:</p>\n\n<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>\n\n<p><a href=\"https://ai-composition-recognition2020.github.io/english.html\">https://ai-composition-recognition2020.github.io/english.html</a>&nbsp;(English instruction)</p>", 
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    "title": "The development dataset of  the AI composition recognition competition, CSMT2020", 
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    "publication_date": "2020-07-15", 
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        "affiliation": "Beijing University of Posts and Telecommunications", 
        "name": "Jing, Yinji"
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        "affiliation": "Beijing University of Posts and Telecommunications", 
        "name": "Li, Shengchen"
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        "affiliation": "Beijing Zhongwen Law Firm", 
        "name": "Zhou, Wei"
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        "affiliation": "Beijing Acoustics Society", 
        "name": "Zhu, Yidan"
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        "affiliation": "China Conservatory of Music", 
        "name": "Li, Zijin"
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        "affiliation": "Queen Mary University of London", 
        "name": "Fazekas, George"
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        "affiliation": "Beijing University of Posts and Telecommunications", 
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