Automatic identification of bird species based on sinusoidal modeling of syllables

Aki Härmä

Automatic identification of bird species based on sinusoidal modeling of syllables

^*Corresponding author for this work

Research output: Contribution to journal › Conference article in journal › Academic › peer-review

Abstract

Syllables are elementary building blocks of bird song. In sounds of many songbirds a large class of syllables can be approximated as amplitude and frequency varying brief sinusoidal pulses. In this article 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.

Original language	English
Pages (from-to)	545-548
Number of pages	4
Journal	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	5
Publication status	Published - 2003
Externally published	Yes
Event	2003 IEEE International Conference on Accoustics, Speech, and Signal Processing - Hong Kong, Hong Kong Duration: 6 Apr 2003 → 10 Apr 2003

Cite this

@article{7d287cfd7c624db49e66106df780a7ea,

title = "Automatic identification of bird species based on sinusoidal modeling of syllables",

abstract = "Syllables are elementary building blocks of bird song. In sounds of many songbirds a large class of syllables can be approximated as amplitude and frequency varying brief sinusoidal pulses. In this article 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.",

author = "Aki H{\"a}rm{\"a}",

year = "2003",

language = "English",

volume = "5",

pages = "545--548",

journal = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",

issn = "1520-6149",

publisher = "IEEE",

note = "2003 IEEE International Conference on Accoustics, Speech, and Signal Processing ; Conference date: 06-04-2003 Through 10-04-2003",

}

TY - JOUR

T1 - Automatic identification of bird species based on sinusoidal modeling of syllables

AU - Härmä, Aki

PY - 2003

Y1 - 2003

N2 - Syllables are elementary building blocks of bird song. In sounds of many songbirds a large class of syllables can be approximated as amplitude and frequency varying brief sinusoidal pulses. In this article 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.

AB - Syllables are elementary building blocks of bird song. In sounds of many songbirds a large class of syllables can be approximated as amplitude and frequency varying brief sinusoidal pulses. In this article 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.

UR - http://www.scopus.com/inward/record.url?scp=0141855203&partnerID=8YFLogxK

M3 - Conference article in journal

AN - SCOPUS:0141855203

SN - 1520-6149

VL - 5

SP - 545

EP - 548

JO - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

JF - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

T2 - 2003 IEEE International Conference on Accoustics, Speech, and Signal Processing

Y2 - 6 April 2003 through 10 April 2003

ER -

Automatic identification of bird species based on sinusoidal modeling of syllables

Abstract

Other files and links

Fingerprint

Cite this