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TUT Rare sound events, Development dataset

Diment, Aleksandr; Mesaros, Annamaria; Heittola, Toni; Virtanen, Tuomas


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    "description": "<p>TUT Rare Sound events 2017, development dataset consists of source files for creating mixtures of rare sound events (classes baby cry, gun shot, glass break) with background audio, as well a set of readily generated mixtures and recipes for generating them.</p>\n\n<p>The &quot;source&quot; part of the dataset consists of two subsets:</p>\n\n<ul>\n\t<li>background recordings from 15 different acoustic scenes,</li>\n\t<li>recordings with the target rare sound events from three classes, accompanied by annotations of their temporal occurrences,</li>\n\t<li>a set of meta files providing the cross-validation setup: lists of background and target event recordings split into training and test subsets (called &quot;devtrain&quot; and &quot;devtest&quot;, respectively, indicating they are provided as the development dataset, as opposed to the evaluation dataset released separately).&nbsp;</li>\n</ul>\n\n<p>The mixture set consists of two subsets (training and testing), each containing ~1500 mixtures (~500 per target class in each subset, with half of the mixtures not containing any target class events).&nbsp;</p>\n\n<p>&nbsp;</p>\n\n<p>The collection of the background recording data has been financially supported by European Research Council under the European Unions H2020 Framework Programme through ERC Grant Agreement 637422 EVERYSOUND.</p>", 
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        "affiliation": "Tampere University of Technology", 
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        "affiliation": "Tampere University of Technology", 
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        "affiliation": "Tampere University of Technology", 
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        "name": "Diment, Aleksandr"
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    "references": [
      "Annamaria Mesaros, Toni Heittola, Aleksandr Diment, Benjamin Elizalde, Ankit Shah, Emmanuel Vincent, Bhiksha Raj, and Tuomas Virtanen. DCASE 2017 challenge setup: tasks, datasets and baseline system. In Proceedings of the Detection and Classification of Acoustic Scenes and Events 2017 Workshop (DCASE2017), pp 85\u201392. November 2017."
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    "keywords": [
      "computational auditory scene analysis", 
      "sound event detection", 
      "audio", 
      "rare events"
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    "publication_date": "2017-03-21", 
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        "affiliation": "Tampere University of Technology", 
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