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TUT Rare sound events, Development dataset

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


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    <dcat:keyword>computational auditory scene analysis</dcat:keyword>
    <dcat:keyword>sound event detection</dcat:keyword>
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    <dct:description>&lt;p&gt;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.&lt;/p&gt; &lt;p&gt;The &amp;quot;source&amp;quot; part of the dataset consists of two subsets:&lt;/p&gt; &lt;ul&gt; &lt;li&gt;background recordings from 15 different acoustic scenes,&lt;/li&gt; &lt;li&gt;recordings with the target rare sound events from three classes, accompanied by annotations of their temporal occurrences,&lt;/li&gt; &lt;li&gt;a set of meta files providing the cross-validation setup: lists of background and target event recordings split into training and test subsets (called &amp;quot;devtrain&amp;quot; and &amp;quot;devtest&amp;quot;, respectively, indicating they are provided as the development dataset, as opposed to the evaluation dataset released separately).&amp;nbsp;&lt;/li&gt; &lt;/ul&gt; &lt;p&gt;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).&amp;nbsp;&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt; &lt;p&gt;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.&lt;/p&gt;</dct:description>
    <dct:description xml:lang="">The license terms are specified in the LICENSE.txt file.</dct:description>
    <dct:description xml:lang="">{"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."]}</dct:description>
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    <dct:title>Computational Analysis of Everyday Soundscapes</dct:title>
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