@proceedings {57606,
	title = {Automatic Segmentation of Ultrasonic Vocalizations in Rodents},
	year = {2019},
	publisher = {Springer International Publishing},
	address = {Cham},
	abstract = {<p>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.</p>
<p>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.</p>
},
	isbn = {978-3-030-31634-1},
	doi = {10.1007/978-3-030-31635-810.1007/978-3-030-31635-8_5},
	url = {http://link.springer.com/10.1007/978-3-030-31635-8},
	author = {Pessoa, Diogo and Petrella, Lorena and Castelo-Branco, Miguel and Teixeira, C{\'e}sar},
	editor = {Henriques, Jorge and Neves, Nuno and de Carvalho, Paulo}
}
