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dc.contributor.authorAndreas, Jacob
dc.contributor.authorBeguš, Gašper
dc.contributor.authorBronstein, Michael M
dc.contributor.authorDiamant, Roee
dc.contributor.authorDelaney, Denley
dc.contributor.authorGero, Shane
dc.contributor.authorGoldwasser, Shafi
dc.contributor.authorGruber, David F
dc.contributor.authorde Haas, Sarah
dc.contributor.authorMalkin, Peter
dc.contributor.authorPavlov, Nikolay
dc.contributor.authorPayne, Roger
dc.contributor.authorPetri, Giovanni
dc.contributor.authorRus, Daniela
dc.contributor.authorSharma, Pratyusha
dc.contributor.authorTchernov, Dan
dc.contributor.authorTønnesen, Pernille
dc.contributor.authorTorralba, Antonio
dc.contributor.authorVogt, Daniel
dc.contributor.authorWood, Robert J
dc.date.accessioned2022-07-18T18:56:46Z
dc.date.available2022-07-18T18:56:46Z
dc.date.issued2022-06
dc.identifier.urihttps://hdl.handle.net/1721.1/143834
dc.description.abstractMachine 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.en_US
dc.language.isoen
dc.publisherElsevier BVen_US
dc.relation.isversionof10.1016/j.isci.2022.104393en_US
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivs Licenseen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.sourceElsevieren_US
dc.titleToward understanding the communication in sperm whalesen_US
dc.typeArticleen_US
dc.identifier.citationAndreas, Jacob, Beguš, Gašper, Bronstein, Michael M, Diamant, Roee, Delaney, Denley et al. 2022. "Toward understanding the communication in sperm whales." iScience, 25 (6).
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
dc.relation.journaliScienceen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2022-07-18T18:30:01Z
dspace.orderedauthorsAndreas, J; Beguš, G; Bronstein, MM; Diamant, R; Delaney, D; Gero, S; Goldwasser, S; Gruber, DF; de Haas, S; Malkin, P; Pavlov, N; Payne, R; Petri, G; Rus, D; Sharma, P; Tchernov, D; Tønnesen, P; Torralba, A; Vogt, D; Wood, RJen_US
dspace.date.submission2022-07-18T18:30:05Z
mit.journal.volume25en_US
mit.journal.issue6en_US
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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