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TUT Acoustic Scenes 2017 Features

Heittola, Toni; Mesaros, Annamaria; Virtanen, Tuomas


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    "description": "<p>TUT Acoustic Scenes features dataset consists of feature matrices extracted for 10-seconds audio segments from 15 acoustic scenes:&nbsp;</p>\n\n<ul>\n\t<li>Bus - traveling by bus in the city (vehicle)</li>\n\t<li>Cafe / Restaurant - small cafe/restaurant (indoor)</li>\n\t<li>Car - driving or traveling as a passenger, in the city (vehicle)</li>\n\t<li>City center (outdoor)</li>\n\t<li>Forest path (outdoor)</li>\n\t<li>Grocery store - medium size grocery store (indoor)</li>\n\t<li>Home (indoor)</li>\n\t<li>Lakeside beach (outdoor)</li>\n\t<li>Library (indoor)</li>\n\t<li>Metro station (indoor)</li>\n\t<li>Office - multiple persons, typical work day (indoor)</li>\n\t<li>Residential area (outdoor)</li>\n\t<li>Train (traveling, vehicle)</li>\n\t<li>Tram (traveling, vehicle)</li>\n\t<li>Urban park (outdoor)</li>\n</ul>\n\n<p>Dataset is split into **Train set** and **Test set**. Each acoustic scene in the Train set has 300 segments, and Test set has 100 segments. The dataset contains similar material to other TUT Acoustic Scenes 2017 datasets: TUT Acoustic Scenes 2017 development dataset and TUT Acoustic Scenes 2017 evaluation dataset. All these &nbsp;datasets are composed from same pool of original audio recordings, but exact audio segments selected for the datasets differ.&nbsp;</p>", 
    "contributors": [
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        "affiliation": "Tampere University of Technology", 
        "type": "DataCollector", 
        "name": "Fagerlund, Eemi"
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        "affiliation": "Tampere University of Technology", 
        "type": "DataCollector", 
        "name": "Hiltunen, Aku"
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        "title": "Computational Analysis of Everyday Soundscapes", 
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    "keywords": [
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    "publication_date": "2018-07-31", 
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        "name": "Heittola, Toni"
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        "affiliation": "Tampere University of Technology", 
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