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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Chabout, J., Sarkar, A., Dunson, D.B., Jarvis, E.D.: Male mice song syntax depends on social contexts and influences female preferences. Front. Behav. Neurosci. 9, 1–16 (2015)
Coffey, K.R., Marx, R.G., Neumaier, J.F.: DeepSqueak: a deep learning-based system for detection and analysis of ultrasonic vocalizations. Neuropsychopharmacology 44, 859–868 (2019)
Grimsley, J.M.S., Monaghan, J.J.M., Wenstrup, J.J.: Development of social vocalizations in mice. PLoS ONE 6(3), e17460 (2011)
Harma, A.: Automatic identification of bird species based on sinusoidal modeling of syllables. In: 2003 IEEE International Conference on Acoustics Speech, Signal Processing 2003, Proceedings, (ICASSP 2003), vol. 5, p. V–545–8. IEEE (2004)
Holy, T.E., Guo, Z.: Ultrasonic songs of male mice. PLoS Biol. 3(12), e386 (2005)
Ivanenko, A., Watkins, P., van Gerven, M.A.J., Hammerschmidt, K., Englitz, B.: Classification of mouse ultrasonic vocalizations using deep learning. bioRxiv, p. 358143, January 2018
MathWorks: Spectral entropy (2019)
Portfors, C.V.: Types and functions of ultrasonic vocalizations in laboratory rats and mice. J. Am. Assoc. Lab. Anim. Sci. 46(1), 28–34 (2007)
Potamitis, I., Ntalampiras, S., Jahn, O., Riede, K.: Automatic bird sound detection in long real-field recordings: applications and tools. Appl. Acoust. 80, 1–9 (2014)
Scattoni, M.L., Gandhy, S.U., Ricceri, L., Crawley, J.N.: Unusual repertoire of vocalizations in the BTBR T+tf/J mouse model of autism. PLoS ONE 3(8), e3067 (2008)
Vajda, S., Shannon, C.E., Weaver, W.: The mathematical theory of communication. Math. Gaz. 34(310), 312 (1950)
Vinet, L., Zhedanov, A.: Rodent Bioacoustics. Springer Handbook of Auditory Research, vol. 67. Springer International Publishing, Cham (2018)
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.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/978-3-030-31635-8_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-31634-1
Online ISBN: 978-3-030-31635-8
eBook Packages: EngineeringEngineering (R0)