Dataset Open Access
Theodoros Giannakopoulos; Stasinos Konstantopoulos
<?xml version='1.0' encoding='utf-8'?> <resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd"> <identifier identifierType="DOI">10.5281/zenodo.376480</identifier> <creators> <creator> <creatorName>Theodoros Giannakopoulos</creatorName> <affiliation>NCSR Demokritos</affiliation> </creator> <creator> <creatorName>Stasinos Konstantopoulos</creatorName> <affiliation>NCSR Demokritos</affiliation> </creator> </creators> <titles> <title>A dataset for high-level activity recognition based on low level audio events</title> </titles> <publisher>Zenodo</publisher> <publicationYear>2017</publicationYear> <dates> <date dateType="Issued">2017-03-10</date> </dates> <resourceType resourceTypeGeneral="Dataset"/> <alternateIdentifiers> <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/376480</alternateIdentifier> </alternateIdentifiers> <relatedIdentifiers> <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/radio</relatedIdentifier> </relatedIdentifiers> <rightsList> <rights rightsURI="http://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights> <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights> </rightsList> <descriptions> <description descriptionType="Abstract"><p>The high level activities are:<br> - kitchencleanup<br> - music<br> - no activity<br> - other activity<br> - talk<br> - tv</p> <p>Each recording of low-level audio events is stored in a separate file.</p> <p>Files are organized in 6 folders, each folder corresponding to a separate file.</p> <p>The format of is file is json-like. In particular, each row has the following format:</p> <p>{"prob": 0.88557562121157585, "energy": 0.024511212402412885, "t": 1485110417, "event": "speech"}</p> <p>This dataset can be evaluated with the python code metaClassifier/evaluate.py of the AUOR repository:<br> https://github.com/tyiannak/AUROS</p></description> </descriptions> <fundingReferences> <fundingReference> <funderName>European Commission</funderName> <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier> <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/643892/">643892</awardNumber> <awardTitle>Robots in assisted living environments: Unobtrusive, efficient, reliable and modular solutions for independent ageing</awardTitle> </fundingReference> </fundingReferences> </resource>
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