| 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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