Automatic classification of mice vocalizations using Machine Learning techniques and Convolutional Neural Networks
Open Access
- 19 January 2021
- journal article
- research article
- Published by Public Library of Science (PLoS) in PLOS ONE
- Vol. 16 (1), e0244636
- https://doi.org/10.1371/journal.pone.0244636
Abstract
Ultrasonic vocalizations (USVs) analysis is a well-recognized tool to investigate animal communication. It can be used for behavioral phenotyping of murine models of different disorders. The USVs are usually recorded with a microphone sensitive to ultrasound frequencies and they are analyzed by specific software. Different calls typologies exist, and each ultrasonic call can be manually classified, but the qualitative analysis is highly time-consuming. Considering this framework, in this work we proposed and evaluated a set of supervised learning methods for automatic USVs classification. This could represent a sustainable procedure to deeply analyze the ultrasonic communication, other than a standardized analysis. We used manually built datasets obtained by segmenting the USVs audio tracks analyzed with the Avisoft software, and then by labelling each of them into 10 representative classes. For the automatic classification task, we designed a Convolutional Neural Network that was trained receiving as input the spectrogram images associated to the segmented audio files. In addition, we also tested some other supervised learning algorithms, such as Support Vector Machine, Random Forest and Multilayer Perceptrons, exploiting informative numerical features extracted from the spectrograms. The performance showed how considering the whole time/frequency information of the spectrogram leads to significantly higher performance than considering a subset of numerical features. In the authors’ opinion, the experimental results may represent a valuable benchmark for future work in this research field.This publication has 30 references indexed in Scilit:
- Automating ultrasonic vocalization analyses: The WAAVES programJournal of Neuroscience Methods, 2013
- Absence of CNTNAP2 Leads to Epilepsy, Neuronal Migration Abnormalities, and Core Autism-Related DeficitsCell, 2011
- Ultrasonic vocalizations in mouse models for speech and socio-cognitive disorders: insights into the evolution of vocal communicationGenes, Brain and Behavior, 2010
- Ultrasonic vocalizations: A tool for behavioural phenotyping of mouse models of neurodevelopmental disordersNeuroscience & Biobehavioral Reviews, 2009
- Unusual Repertoire of Vocalizations in the BTBR T+tf/J Mouse Model of AutismPLOS ONE, 2008
- Affiliative Behavior, Ultrasonic Communication and Social Reward Are Influenced by Genetic Variation in Adolescent MicePLOS ONE, 2007
- Ultrasonic Songs of Male MicePLoS Biology, 2005
- Pups Call, Mothers Rush: Does Maternal Responsiveness Affect the Amount of Ultrasonic Vocalizations in Mouse Pups?Behavior Genetics, 2005
- Support-vector networksMachine Learning, 1995
- Principles of Neurodynamics: Perceptrons and the Theory of Brain MechanismsThe American Journal of Psychology, 1963