Detail publikace

Automatic bird species recognition based on birds vocalization

ŠŤASTNÝ, J. MUNK, M. JURÁNEK, L.

Originální název

Automatic bird species recognition based on birds vocalization

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

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%.

Klíčová slova

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

Autoři

ŠŤASTNÝ, J.; MUNK, M.; JURÁNEK, L.

Vydáno

14. 12. 2018

Nakladatel

Springer Nature

ISSN

1687-4722

Periodikum

Eurasip Journal on Audio, Speech, and Music Processing

Ročník

2018

Číslo

12

Stát

Švýcarská konfederace

Strany od

1

Strany do

7

Strany počet

7

URL

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

Plný text v Digitální knihovně

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"
}