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TUT Acoustic scenes 2016, Evaluation dataset

Mesaros, Annamaria; Heittola, Toni; Virtanen, Tuomas


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<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:contributor>Fagerlund, Eemi</dc:contributor>
  <dc:contributor>Hiltunen, Aku</dc:contributor>
  <dc:contributor>Heittola, Toni</dc:contributor>
  <dc:creator>Mesaros, Annamaria</dc:creator>
  <dc:creator>Heittola, Toni</dc:creator>
  <dc:creator>Virtanen, Tuomas</dc:creator>
  <dc:date>2016-11-10</dc:date>
  <dc:description>TUT Acoustic Scenes 2016, evaluation dataset consists of 30-seconds audio segments from 15 acoustic scenes:


	Bus - traveling by bus in the city (vehicle)
	Cafe / Restaurant - small cafe/restaurant (indoor)
	Car - driving or traveling as a passenger, in the city (vehicle)
	City center (outdoor)
	Forest path (outdoor)
	Grocery store - medium size grocery store (indoor)
	Home (indoor)
	Lakeside beach (outdoor)
	Library (indoor)
	Metro station (indoor)
	Office - multiple persons, typical work day (indoor)
	Residential area (outdoor)
	Train (traveling, vehicle)
	Tram (traveling, vehicle)
	Urban park (outdoor)


Each acoustic scene has 26 segments totaling 13 minutes of audio.</dc:description>
  <dc:identifier>https://zenodo.org/record/165995</dc:identifier>
  <dc:identifier>10.5281/zenodo.165995</dc:identifier>
  <dc:identifier>oai:zenodo.org:165995</dc:identifier>
  <dc:relation>info:eu-repo/grantAgreement/EC/H2020/637422/</dc:relation>
  <dc:relation>url:https://zenodo.org/communities/tut-arg</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:subject>computational auditory scene analysis</dc:subject>
  <dc:subject>acoustic scene classification</dc:subject>
  <dc:subject>audio</dc:subject>
  <dc:title>TUT Acoustic scenes 2016, Evaluation dataset</dc:title>
  <dc:type>info:eu-repo/semantics/other</dc:type>
  <dc:type>dataset</dc:type>
</oai_dc:dc>
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