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Comparing classification methodologies

Comparing methodologies for classification of zebra finch distance calls

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Background

Bioacoustic analysis has been used for a variety of purposes including classifying vocalizations for biodiversity monitoring and understanding mechanisms of cognitive processes. A wide range of statistical methods, including various automated methods, have been used to successfully classify vocalizations based on species, sex, geography, and individual. A comprehensive approach focusing on identifying acoustic features putatively involved in classification is required for the prediction of features necessary for discrimination in the real world.

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What?

Classified zebra finch distance calls based on sex with several methods like DFAs, SVMs & ANNs and compared across methodologies.

Why?

Comparisons will help understanding features responsible for the classification and provide us options to choose a classification method.

Results

All methods used here classified the calls with high accuracy.