Clemins, P: Automatic Classification of Animal Vocalizations
(Sprache: Englisch)
This manuscript describes a framework for theanalysis andclassification of animal vocalizations. Theframework combines generalized perceptual linearprediction (gPLP) features, which incorporateinformation about the ability of the species understudy to...
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This manuscript describes a framework for theanalysis andclassification of animal vocalizations. Theframework combines generalized perceptual linearprediction (gPLP) features, which incorporateinformation about the ability of the species understudy to perceive sounds, and a hidden Markov model(HMM) classification system. The effectiveness ofthe framework is shown by analyzing African elephant andbeluga whale vocalizations. The features extractedfrom the African elephant data are used as input to asupervised classification system and compared toresults from traditional statistical tests. The gPLPfeatures extracted from the beluga whale data areused in an unsupervised classification system and theresults are compared to labels assigned by experts. The development of a framework from which to buildanimal vocalization classifiers will providebioacoustics researchers with a consistent platformto analyze and classify vocalizations.
Autoren-Porträt von Patrick Clemins
Patrick received his bachelors, masters, and doctorate inElectrical and Computer Engineering from Marquette University,focusing on machine learning and digital signal processing. While working on this dissertation research, he also taughtpart-time and served as President of the alumni board for theMarquette Chapter of Triangle Fraternity.
Bibliographische Angaben
- Autor: Patrick Clemins
- 2009, 152 Seiten, Maße: 15 x 22 cm, Kartoniert (TB), Englisch
- Verlag: VDM Verlag
- ISBN-10: 363914581X
- ISBN-13: 9783639145816
Sprache:
Englisch
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