TUT Rare sound events, Development dataset

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

doi:10.5281/zenodo.401395

March 21, 2017 Dataset Open Access

TUT Rare sound events, Development dataset

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

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    <subfield code="a">&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;</subfield>
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Views	4,567	4,567
Downloads	67,760	67,760
Data volume	65.6 TB	65.6 TB
Unique views	3,618	3,618
Unique downloads	8,179	8,179

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Publication date:

March 21, 2017

DOI:

Keyword(s):

computational auditory scene analysis sound event detection audio rare events

Grants:

European Commission:

EVERYSOUND - Computational Analysis of Everyday Soundscapes (637422)

Communities:

Tampere University, Audio Research Group

License (for files):

Other (Non-Commercial)

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Version 1 10.5281/zenodo.401395

Mar 21, 2017

Cite all versions? You can cite all versions by using the DOI 10.5281/zenodo.603106. This DOI represents all versions, and will always resolve to the latest one. Read more.

TUT Rare sound events, Development dataset

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