Automatic Segmentation of Ultrasonic Vocalizations in Rodents

Publication Type:Conference Paper
Year of Publication:2019
Autores:Pessoa, Petrella, Castelo-Branco, Teixeira
Editor:Henriques, Neves, de Carvalho
Publisher:Springer International Publishing
Conference Location:Cham
ISBN Number:978-3-030-31634-1
Palabras clave:Rodents ultrasonic vocalizations, Signal processing, Signal segmentation, Spectral Entropy
Resumen:

Ultrasonic vocalizations studies in rodents have increasingly drawn researchers attention as it have been considered a powerful tool to understand the animals behavior and their interactions in different social and environmental contexts.

This paper presents an entropy-based algorithm for accurate and robust segmentation of mouse ultrasonic calls. Instead of using the conventional energy-based features, the spectral entropy is developed to identify the audio segments accurately. The new approach for mice calls detection has been able to detect up to 97% of the vocalizations.

URL:http://link.springer.com/10.1007/978-3-030-31635-8
DOI:10.1007/978-3-030-31635-810.1007/978-3-030-31635-8_5
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Scratchpads developed and conceived by (alphabetical): Ed Baker, Katherine Bouton Alice Heaton Dimitris Koureas, Laurence Livermore, Dave Roberts, Simon Rycroft, Ben Scott, Vince Smith