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| Paper: | MLSP-P4.9 |
| Session: | Machine Learning Applications |
| Time: | Thursday, May 20, 09:30 - 11:30 |
| Presentation: |
Poster |
| Topic: |
Machine Learning for Signal Processing: Bioinformatics Applications |
| Title: |
CLASSIFICATION OF THE HARMONIC STRUCTURE IN BIRD VOCALIZATION |
| Authors: |
Aki Härmä; Helsinki University of Technology | | |
| | Panu Somervuo; Helsinki University of Technology | | |
| Abstract: |
This article is related to the development of techniques for automatic recognition of bird species by their sounds. It has been demonstrated earlier that a simple model of one time-varying sinusoid is very useful in classification and recognition of typical bird sounds. However, a large class of bird sounds are not pure sinusoids but have a clear harmonic spectrum structure. In this article, we introduce a way to classify bird syllables into four classes by their harmonic structure. |
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