DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Jünemann, Klaus | - |
dc.contributor.author | Smekhunov, Sergey | |
dc.date.accessioned | 2020-09-29T14:38:38Z | - |
dc.date.available | 2020-09-29T14:38:38Z | - |
dc.date.created | 2018 | |
dc.date.issued | 2018-06-01 | |
dc.identifier.uri | http://hdl.handle.net/20.500.12738/8339 | - |
dc.description.abstract | The goal of the present document is to investigate signal processing techniques present in music information retrieval (MIR) in the context of emotion recognition in instrumental music. For this purpose machine learning techniques are employed and classifier is trained. Output of the classifier is used to estimate the efficiency and the contribution of each individual signal feature. | en |
dc.description.abstract | Das Ziel des vorliegenden Dokuments ist es, Signalverarbeitungstechniken zu untersuchen, die bei der Musikinformationsgabruf (MIR) im Kontext der Emotionserkennung in der Instrumentalmusik vorhanden sind. Zu diesem Zweck werden maschinelle Lerntechniken eingesetzt und Klassifikator trainiert. Die Ausgabe des Klassifikators wird verwendet, um die Effizienz und den Beitrag jedes einzelnen Signalmerkmals zu schätzen. | de |
dc.language.iso | en | en |
dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | - |
dc.subject.ddc | 621.3 Elektrotechnik, Elektronik | |
dc.title | Emotion recognition in instrumental music using signal processing and machine learning | en |
dc.title.alternative | Emotion recognition in instrumental music using signal processing and machine learning | en |
dc.type | Thesis | |
openaire.rights | info:eu-repo/semantics/openAccess | |
thesis.grantor.department | Department Informations- und Elektrotechnik | |
thesis.grantor.place | Hamburg | |
thesis.grantor.universityOrInstitution | Hochschule für angewandte Wissenschaften Hamburg | |
tuhh.contributor.referee | Heß, Robert | - |
tuhh.gvk.ppn | 1023646412 | |
tuhh.identifier.urn | urn:nbn:de:gbv:18302-reposit-83419 | - |
tuhh.note.extern | publ-mit-pod | |
tuhh.note.intern | 1 | |
tuhh.oai.show | true | en_US |
tuhh.opus.id | 4276 | |
tuhh.publication.institute | Department Informations- und Elektrotechnik | |
tuhh.type.opus | Bachelor Thesis | - |
dc.subject.gnd | Maschinelles Lernen | |
dc.type.casrai | Supervised Student Publication | - |
dc.type.dini | bachelorThesis | - |
dc.type.driver | bachelorThesis | - |
dc.type.status | info:eu-repo/semantics/publishedVersion | |
dc.type.thesis | bachelorThesis | |
dcterms.DCMIType | Text | - |
tuhh.dnb.status | domain | - |
item.creatorGND | Smekhunov, Sergey | - |
item.fulltext | With Fulltext | - |
item.creatorOrcid | Smekhunov, Sergey | - |
item.grantfulltext | open | - |
item.cerifentitytype | Publications | - |
item.advisorGND | Jünemann, Klaus | - |
item.languageiso639-1 | en | - |
item.openairecristype | http://purl.org/coar/resource_type/c_46ec | - |
item.openairetype | Thesis | - |
Appears in Collections: | Theses |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Abschluessarbeit_Smekhunov_Sergey.pdf | 1.23 MB | Adobe PDF | View/Open |
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