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

Research output: Contribution to journalReview articlepeer-review

Abstract

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.

Original languageEnglish
Article number104393
JournaliScience
Volume25
Issue number6
DOIs
StatePublished - 17 Jun 2022

Bibliographical note

Funding Information:
We thank Jane Lipson, Pietro Liò, Philippe Schlenker, Emmanuel Chemla, and Camille Coye for helpful comments on the manuscript. This study was funded by grants from Dalio Philanthropies and Ocean X ; Sea Grape Foundation ; Rosamund Zander/Hansjorg Wyss, Chris Anderson/Jacqueline Novogratz through The Audacious Project: a collaborative funding initiative housed at TED; as well as support from National Geographic Society Grant (No. NGS-72337T-20 ) and Lyda Hill Philanthropies .

Publisher Copyright:
© 2022 The Authors

Keywords

  • Artificial intelligence
  • Ethology
  • Linguistics
  • Natural language processing

ASJC Scopus subject areas

  • General

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