Musical Instrument Activity Detection using Self-Supervised Learning and Domain Adaptation

Musical Instrument Activity Detection using Self-Supervised Learning and Domain Adaptation

With the ever growing media and music catalogs, tools that search and navigate this data are important. For more complex search queries, meta-data is needed, but to manually label the vast amounts of new content is impossible. In this thesis, automatic labeling of musical instrument activities in so...

Full description

Bibliographic Details
Main Author: Nyströmer, Carl
Format: Others
Language:English
Published: KTH, Skolan för elektroteknik och datavetenskap (EECS) 2020
Subjects:
Audio classification
music information retrieval
musical instrument recognition
musical instrument activity detection
self-supervised learning
domain adaptation
Ljudklassificering
hämtning av musikinformation
musikintrumentsigenkänning
instrumentaktivitetsigenkänning
självövervakad inlärning
domänadaption
Computer Sciences
Datavetenskap (datalogi)
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-280810

Internet

http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-280810

Similar Items