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EMOPIA: A Multi-Modal Pop Piano Dataset For Emotion Recognition and Emotion-based Music Generation

Hung, Hsiao-Tzu; Ching, Joann; Doh, Seungheon; Kim, Nabin; Nam, Juhan; Yang, Yi-Hsuan


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{
  "description": "<p>EMOPIA (pronounced &lsquo;yee-m&ograve;-pi-uh&rsquo;) dataset is a shared multi-modal (audio and MIDI) database focusing on perceived emotion in&nbsp;<strong>pop piano music</strong>, to facilitate research on various tasks related to music emotion. The dataset contains&nbsp;<strong>1,087</strong>&nbsp;music clips from 387 songs and&nbsp;<strong>clip-level</strong>&nbsp;emotion labels annotated by four dedicated annotators.&nbsp;</p>\n\n<p>For more detailed information about the dataset, please refer to our paper:&nbsp;<a href=\"https://arxiv.org/abs/2108.01374\"><strong>EMOPIA: A Multi-Modal Pop Piano Dataset For Emotion Recognition and Emotion-based Music Generation</strong></a>.&nbsp;</p>\n\n<p><strong>File Description</strong></p>\n\n<ul>\n\t<li><em><strong>midis/</strong></em>:&nbsp;midi clips transcribed using GiantMIDI.\n\n\t<ul>\n\t\t<li>Filename `Q1_xxxxxxx_2.mp3`: Q1 means this clip belongs to Q1 on the V-A space; xxxxxxx is the song ID on YouTube, and the `2` means this clip is the 2nd clip taken from the full song.</li>\n\t</ul>\n\t</li>\n\t<li><em><strong>metadata/</strong></em>:&nbsp;metadata from YouTube. (Got when crawling)</li>\n\t<li>\n\t<p><em><strong>songs_lists/</strong></em>:&nbsp;YouTube URLs of songs.</p>\n\t</li>\n\t<li>\n\t<p><em><strong>tagging_lists/</strong></em>:&nbsp;raw tagging result for each sample.</p>\n\t</li>\n\t<li>\n\t<p><em><strong>label.csv</strong></em>: metadata that records filename, clip timestamps, and annotator.</p>\n\t</li>\n\t<li>\n\t<p><em><strong>metadata_by_song.csv</strong></em>: list all the clips by the song. Can be used to create the train/val/test splits to avoid the same song appear in both train and test.</p>\n\t</li>\n\t<li>\n\t<p><em><strong>scripts/prepare_split.ipynb:</strong></em> the script to create train/val/test splits and save them to csv files.</p>\n\t</li>\n</ul>\n\n<p>&nbsp;</p>\n\n<p><strong>Cite this dataset</strong></p>\n\n<pre><code>@inproceedings{{EMOPIA},\n         author = {Hung, Hsiao-Tzu and Ching, Joann and Doh, Seungheon and Kim, Nabin and Nam, Juhan and Yang, Yi-Hsuan},\n         title = {{MOPIA}: A Multi-Modal Pop Piano Dataset For Emotion Recognition and Emotion-based Music Generation},\n         booktitle = {Proc. Int. Society for Music Information Retrieval Conf.},\n         year = {2021}\n}</code></pre>", 
  "license": "https://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "Academia Sinica", 
      "@type": "Person", 
      "name": "Hung, Hsiao-Tzu"
    }, 
    {
      "affiliation": "Academia Sinica", 
      "@type": "Person", 
      "name": "Ching, Joann"
    }, 
    {
      "affiliation": "KAIST", 
      "@type": "Person", 
      "name": "Doh, Seungheon"
    }, 
    {
      "affiliation": "Georgia Institute of Technology", 
      "@type": "Person", 
      "name": "Kim, Nabin"
    }, 
    {
      "affiliation": "KAIST", 
      "@id": "https://orcid.org/0000-0003-2664-2119", 
      "@type": "Person", 
      "name": "Nam, Juhan"
    }, 
    {
      "affiliation": "Academia Sinica", 
      "@id": "https://orcid.org/0000-0002-2724-6161", 
      "@type": "Person", 
      "name": "Yang, Yi-Hsuan"
    }
  ], 
  "url": "https://zenodo.org/record/5090631", 
  "datePublished": "2021-07-18", 
  "version": "1.0", 
  "@type": "Dataset", 
  "keywords": [
    "piano", 
    "emotion", 
    "music", 
    "midi"
  ], 
  "@context": "https://schema.org/", 
  "distribution": [
    {
      "contentUrl": "https://zenodo.org/api/files/6746dc58-353e-4aef-8f6e-494dd97975cb/EMOPIA_1.0.zip", 
      "encodingFormat": "zip", 
      "@type": "DataDownload"
    }
  ], 
  "identifier": "https://doi.org/10.5281/zenodo.5090631", 
  "@id": "https://doi.org/10.5281/zenodo.5090631", 
  "workFeatured": {
    "url": "https://ismir2021.ismir.net/", 
    "alternateName": "ISMIR", 
    "@type": "Event", 
    "name": "International Society for Music Information Retrieval Conference 2021"
  }, 
  "name": "EMOPIA: A Multi-Modal Pop Piano Dataset For Emotion Recognition and Emotion-based Music Generation"
}
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