Automatic bird species recognition based on birds vocalization
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, ClassificationTrvalý odkaz
http://hdl.handle.net/11012/137370Typ dokumentu
Recenzovaný dokumentVerze dokumentu
Finální verze PDFZdrojový dokument
Eurasip Journal on Audio, Speech, and Music Processing. 2018, vol. 2018, issue 12, p. 1-7.http://link.springer.com/article/10.1186/s13636-018-0143-7