Publication detail

Automatic bird species recognition based on birds vocalization

ŠŤASTNÝ, J. MUNK, M. JURÁNEK, L.

Original Title

Automatic bird species recognition based on birds vocalization

Type

journal article in Web of Science

Language

English

Original Abstract

This paper deals with a project of Automatic Bird Species Recognition Based on Bird Vocalization. Eighteen bird species of 6 different families were analyzed. At first, human factor cepstral coefficients representing the given signal were calculated from particular recordings. In the next phase, using the voice activity detection system, segments of bird vocalizations were detected from which a likelihood rate, with which the given code value corresponds to the given model, was calculated using individual hidden Markov models. For each bird species, just one respective hidden Markov model was trained. The interspecific success of 81.2% has been reached. For classification into families, the success has reached 90.45%.

Keywords

HFCC, VAD, kNN, HMM, Bird species recognition, Birdsong recognition, Classification

Authors

ŠŤASTNÝ, J.; MUNK, M.; JURÁNEK, L.

Released

14. 12. 2018

Publisher

Springer Nature

ISBN

1687-4722

Periodical

Eurasip Journal on Audio, Speech, and Music Processing

Year of study

2018

Number

12

State

Swiss Confederation

Pages from

1

Pages to

7

Pages count

7

URL

http://link.springer.com/article/10.1186/s13636-018-0143-7

Full text in the Digital Library

http://hdl.handle.net/11012/137370

BibTex

@article{BUT151882,
  author="Jiří {Šťastný} and Michal {Munk} and Luboš {Juránek}",
  title="Automatic bird species recognition based on birds vocalization",
  journal="Eurasip Journal on Audio, Speech, and Music Processing",
  year="2018",
  volume="2018",
  number="12",
  pages="1--7",
  doi="10.1186/s13636-018-0143-7",
  issn="1687-4722",
  url="http://link.springer.com/article/10.1186/s13636-018-0143-7"
}