DocumentCode
3461179
Title
Automatic identification of bird species based on sinusoidal modeling of syllables
Author
Härmä, Aki
Author_Institution
Lab. of Acoust. & Audio Signal Process., Helsinki Univ. of Technol., Espoo, Finland
Volume
5
fYear
2003
fDate
6-10 April 2003
Abstract
Syllables are elementary building blocks of bird song. In the sounds of many songbirds, a large class of syllables can be approximated as amplitude and frequency varying brief sinusoidal pulses. We test how well bird species can be recognized by comparing simple sinusoidal representations of isolated syllables. Results are encouraging and show that, with limited sets of bird species, a recognizer based on this signal model may already be sufficient.
Keywords
audio signal processing; identification; pattern recognition; signal representation; zoology; biology; bird song; bird species identification; bird species recognition; digital representations; sinusoidal modeling; songbirds; syllables; Acoustic pulses; Acoustic signal processing; Biomedical signal processing; Birds; Energy resolution; Frequency; Humans; Laboratories; Speech; Tongue;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on
ISSN
1520-6149
Print_ISBN
0-7803-7663-3
Type
conf
DOI
10.1109/ICASSP.2003.1200027
Filename
1200027
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