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
Link To Document :
بازگشت