Abstract
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.
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Acknowledgments
This work was supported by FCT fellowship SFRH/BPD/112863/2015 to L.I.P and FLAD Life Sciences 2016, BIGDATIMAGE (CENTRO-01-0145-FEDER, 000016) to M.C.B.
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Pessoa, D., Petrella, L., Castelo-Branco, M., Teixeira, C. (2020). Automatic Segmentation of Ultrasonic Vocalizations in Rodents. In: Henriques, J., Neves, N., de Carvalho, P. (eds) XV Mediterranean Conference on Medical and Biological Engineering and Computing – MEDICON 2019. MEDICON 2019. IFMBE Proceedings, vol 76. Springer, Cham. https://doi.org/10.1007/978-3-030-31635-8_5
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DOI: https://doi.org/10.1007/978-3-030-31635-8_5
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