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MAESTRO Synthetic - Multi-Annotator Estimated Strong Labels

Irene Martin Morato; Manu Harju; Annamaria Mesaros


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  <identifier identifierType="DOI">10.5281/zenodo.5126478</identifier>
  <creators>
    <creator>
      <creatorName>Irene Martin Morato</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-2115-0193</nameIdentifier>
      <affiliation>Tampere University</affiliation>
    </creator>
    <creator>
      <creatorName>Manu Harju</creatorName>
      <affiliation>Tampere University</affiliation>
    </creator>
    <creator>
      <creatorName>Annamaria Mesaros</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-6640-9752</nameIdentifier>
      <affiliation>Tampere University</affiliation>
    </creator>
  </creators>
  <titles>
    <title>MAESTRO Synthetic - Multi-Annotator Estimated Strong Labels</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2021</publicationYear>
  <dates>
    <date dateType="Issued">2021-08-27</date>
  </dates>
  <resourceType resourceTypeGeneral="Dataset"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/5126478</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.5126477</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/machine-listening-tau</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;The dataset was created for studying estimation of strong labels using crowdsourcing.&lt;/p&gt;

&lt;p&gt;It&amp;nbsp;contains 20 synthetic audio files created using Scaper, the reference annotation created with Scaper, and the annotation outcome.&amp;nbsp;Annotation was performed using Amazon Mechanical Turk.&lt;/p&gt;

&lt;p&gt;Audio files contain excerpts of recordings uploaded to freesound.org.(from Urban Sound 8k dataset).&amp;nbsp;Please see FREESOUNDCREDITS.txt for an attribution list.&amp;nbsp;&lt;/p&gt;

&lt;p&gt;The dataset contains:&amp;nbsp;&lt;/p&gt;

&lt;ul&gt;
	&lt;li&gt;audio: the 20 synthetic soundscapes, each 3 min long&lt;/li&gt;
	&lt;li&gt;ground truth:&amp;nbsp; the &amp;quot;true&amp;quot; reference annotation created using Scaper&lt;/li&gt;
	&lt;li&gt;estimated strong labels: the reference annotation created from the crowdsourced data&lt;/li&gt;
	&lt;li&gt;audio tags: the weak labels corresponding to each 10 s segment of the soundscapes, as annotated&lt;/li&gt;
&lt;/ul&gt;

&lt;p&gt;For details on the annotation procedure and label processing methodology, see the following paper:&lt;/p&gt;

&lt;p&gt;Irene Martin&amp;nbsp;Morato, Manu Harju, and Annamaria Mesaros.&amp;nbsp;&lt;em&gt;&lt;a href="https://arxiv.org/abs/2107.12089"&gt;Crowdsourcing strong labels for sound event detection&lt;/a&gt;.&lt;/em&gt;&amp;nbsp;In IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA 2021). New Paltz, NY, Oct 2021.&lt;/p&gt;

&lt;p&gt;&amp;nbsp;&lt;/p&gt;

&lt;p&gt;&amp;nbsp;&lt;/p&gt;</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>Academy of Finland</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100002341</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/AKA//332063/">332063</awardNumber>
      <awardTitle>Teaching machines to listen</awardTitle>
    </fundingReference>
  </fundingReferences>
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