Publication detail

Audio Data Classification by Means of New Algorithms

ŠŤASTNÝ, J. ŠKORPIL, V. FEJFAR, J.

Original Title

Audio Data Classification by Means of New Algorithms

Type

conference paper

Language

English

Original Abstract

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.

Keywords

sound processing, classification, semi-supervised learning, SOM, LVQ, HMM

Authors

ŠŤASTNÝ, J.; ŠKORPIL, V.; FEJFAR, J.

RIV year

2013

Released

2. 7. 2013

Publisher

TSP

Location

Rome, Italy

ISBN

978-1-4799-0402-0

Book

Proceedings of the 36 th International Conference on Telecommunikations and Signal Processing (TSP 2013)

Edition number

1

Pages from

507

Pages to

511

Pages count

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"
}