Automatic identification of bird species based on sinusoidal modeling of syllables

被引：0

作者：

Härmä, A ^{[1
]}

机构：

[1] Helsinki Univ Technol, Lab Acoust & Audio Signal Proc, FIN-02015 Espoo, Finland

来源：

2003 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL V, PROCEEDINGS: SENSOR ARRAY & MULTICHANNEL SIGNAL PROCESSING AUDIO AND ELECTROACOUSTICS MULTIMEDIA SIGNAL PROCESSING | 2003年

关键词：

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

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.

引用

页码：545 / 548

页数：4

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