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ŠŤASTNÝ, J. ŠKORPIL, V. FEJFAR, J.
Originální název
Audio Data Classification by Means of New Algorithms
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
This paper describes classification of sound recordings based on their audio features. This is useful for querying large datasets, searching for recordings with some desired content. We use musical recordings as well as birdsongs recordings, which usually have rich structure and contain a lot of patterns suitable for classification. We present two different classification methods, one for musical recordings and one for birdsongs. These methods are compared and their differences are discussed. In case of musical recordings we use feature vectors describing the recording as a whole piece and we classify these feature vectors with the Self-organizing map and Learning Vector Quantization combination which represent a powerful algorithm using unlabeled as well as labeled data. In case of birdsongs we use feature vectors representing time frames of a recording.
Klíčová slova
sound processing, classification, semi-supervised learning, SOM, LVQ, HMM
Autoři
ŠŤASTNÝ, J.; ŠKORPIL, V.; FEJFAR, J.
Rok RIV
2013
Vydáno
2. 7. 2013
Nakladatel
TSP
Místo
Rome, Italy
ISBN
978-1-4799-0402-0
Kniha
Proceedings of the 36 th International Conference on Telecommunikations and Signal Processing (TSP 2013)
Číslo edice
1
Strany od
507
Strany do
511
Strany počet
5
BibTex
@inproceedings{BUT100910, author="Jiří {Šťastný} and Vladislav {Škorpil} and Jiří {Fejfar}", title="Audio Data Classification by Means of New Algorithms", booktitle="Proceedings of the 36 th International Conference on Telecommunikations and Signal Processing (TSP 2013)", year="2013", number="1", pages="507--511", publisher="TSP", address="Rome, Italy", isbn="978-1-4799-0402-0" }