iScience (Jun 2022)

Toward understanding the communication in sperm whales

  • Jacob Andreas,
  • Gašper Beguš,
  • Michael M. Bronstein,
  • Roee Diamant,
  • Denley Delaney,
  • Shane Gero,
  • Shafi Goldwasser,
  • David F. Gruber,
  • Sarah de Haas,
  • Peter Malkin,
  • Nikolay Pavlov,
  • Roger Payne,
  • Giovanni Petri,
  • Daniela Rus,
  • Pratyusha Sharma,
  • Dan Tchernov,
  • Pernille Tønnesen,
  • Antonio Torralba,
  • Daniel Vogt,
  • Robert J. Wood

Journal volume & issue
Vol. 25, no. 6
p. 104393

Abstract

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Summary: Machine learning has been advancing dramatically over the past decade. Most strides are human-based applications due to the availability of large-scale datasets; however, opportunities are ripe to apply this technology to more deeply understand non-human communication. We detail a scientific roadmap for advancing the understanding of communication of whales that can be built further upon as a template to decipher other forms of animal and non-human communication. Sperm whales, with their highly developed neuroanatomical features, cognitive abilities, social structures, and discrete click-based encoding make for an excellent model for advanced tools that can be applied to other animals in the future. We outline the key elements required for the collection and processing of massive datasets, detecting basic communication units and language-like higher-level structures, and validating models through interactive playback experiments. The technological capabilities developed by such an undertaking hold potential for cross-applications in broader communities investigating non-human communication and behavioral research.

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