Dataset Open Access

A dataset for high-level activity recognition based on low level audio events

Theodoros Giannakopoulos; Stasinos Konstantopoulos


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    <subfield code="a">&lt;p&gt;The high level activities are:&lt;br&gt;
 - kitchencleanup&lt;br&gt;
 - music&lt;br&gt;
 - no activity&lt;br&gt;
 - other activity&lt;br&gt;
 - talk&lt;br&gt;
 - tv&lt;/p&gt;

&lt;p&gt;Each recording of low-level audio events is stored in a separate file.&lt;/p&gt;

&lt;p&gt;Files are organized in 6 folders, each folder corresponding to a separate file.&lt;/p&gt;

&lt;p&gt;The format of is file is json-like. In particular, each row has the following format:&lt;/p&gt;

&lt;p&gt;{"prob": 0.88557562121157585, "energy": 0.024511212402412885, "t": 1485110417, "event": "speech"}&lt;/p&gt;

&lt;p&gt;This dataset can be evaluated with the python code metaClassifier/evaluate.py of the AUOR repository:&lt;br&gt;
https://github.com/tyiannak/AUROS&lt;/p&gt;</subfield>
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