Deep Learning Based Sound Event Recognition

Bajzík, Jakub

Deep Learning Based Sound Event Recognition

but.event.date	25.04.2019	cs
but.event.title	Student EEICT 2019	cs
dc.contributor.author	Bajzík, Jakub
dc.date.accessioned	2020-04-16T07:19:35Z
dc.date.available	2020-04-16T07:19:35Z
dc.date.issued	2019	cs
dc.description.abstract	The main paper deals with the analysis of the methods of processing and recognition of events in the audio signal and the implementation of the selected method in real use. Recognized events are gunshots placed in a background sound such as traffic noise, human voice, animal sounds and other forms of environmental sounds. For events classification and class recognition, the freely available machine learning framework TensorFlow is used.	en
dc.format	text	cs
dc.format.extent	382-385	cs
dc.format.mimetype	application/pdf	en
dc.identifier.citation	Proceedings of the 25st Conference STUDENT EEICT 2019. s. 382-385. ISBN 978-80-214-5735-5	cs
dc.identifier.isbn	978-80-214-5735-5
dc.identifier.uri	http://hdl.handle.net/11012/186698
dc.language.iso	sk	cs
dc.publisher	Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií	cs
dc.relation.ispartof	Proceedings of the 25st Conference STUDENT EEICT 2019	en
dc.relation.uri	http://www.feec.vutbr.cz/EEICT/	cs
dc.rights	© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií	cs
dc.rights.access	openAccess	en
dc.subject	Sound recognition	en
dc.subject	machine learning	en
dc.subject	neural network	en
dc.subject	signal processing	en
dc.title	Deep Learning Based Sound Event Recognition	en
dc.type.driver	conferenceObject	en
dc.type.status	Peer-reviewed	en
dc.type.version	publishedVersion	en
eprints.affiliatedInstitution.department	Fakulta elektrotechniky a komunikačních technologií	cs

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