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ŠŤASTNÝ, J.; MUNK, M.; JURÁNEK, L.
Original Title
Automatic bird species recognition based on birds vocalization
English Title
Type
WoS Article
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%.
English abstract
Keywords
HFCC, VAD, kNN, HMM, Bird species recognition, Birdsong recognition, Classification
Key words in English
Authors
RIV year
2019
Released
14.12.2018
Publisher
Springer Nature
ISBN
1687-4722
Periodical
EURASIP Journal on Audio Speech and Music Processing
Volume
2018
Number
12
State
Swiss Confederation
Pages from
1
Pages to
7
Pages count
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" }
Documents
s13636-018-0143-7