Using machine learning to decode animal communication

Rutz, Christian; Bronstein, Michael; Raskin, Aza; Vernes, Sonja C.; Zacarian, Katherine; Blasi, Damián E.

doi:10.1126/science.adg7314

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Using machine learning to decode animal communication

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Vernes, Sonja C.
Neurogenetics of Vocal Communication Group, MPI for Psycholinguistics, Max Planck Society;
University of St Andrews;

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Rutz, C., Bronstein, M., Raskin, A., Vernes, S. C., Zacarian, K., & Blasi, D. E. (2023). Using machine learning to decode animal communication. Science, 381(6654), 152-155. doi:10.1126/science.adg7314.

Cite as: https://hdl.handle.net/21.11116/0000-000D-71A1-D

Abstract

The past few years have seen a surge of interest in using machine learning (ML) methods for studying the behavior of nonhuman animals (hereafter “animals”) (1). A topic that has attracted particular attention is the decoding of animal communication systems using deep learning and other approaches (2). Now is the time to tackle challenges concerning data availability, model validation, and research ethics, and to embrace opportunities for building collaborations across disciplines and initiatives.