Search

Menu
Search
in Ecology

Dogs’ reactions to motivations and emotions in conspecific and heterospecific vocalizations

115 Views


Abstract

Vocalizations convey information about both emotional valence (negative/positive) and motivational states (hostile/non-hostile). However, it remains unclear which of these dimensions primarily determines what the listener decodes from vocalizations as social messages, guiding their reaction (approach/withdraw). To test this question, we presented agonistic (negative|hostile), play/comfort (positive|non-hostile), and distress sounds (negative|non-hostile) to dogs. In Study 1, the motivational state encoded in conspecific calls better explained dogs’ reactions than emotional valence. Distress calls evoked faster approaches but slower withdrawal than agonistic calls, indicating that dogs primarily decode conspecific social messages based on the caller’s motivation. In Study 2, we tested cross-species decodability with chimpanzee and human calls and speech. Neither the callers’ motivational state nor emotional valence explained dogs’ reactions, which did not support predictions based on Morton’s rules and other proposed universal principles of emotion encoding. These findings suggest that the caller’s motivation may have been more significant in close-contact call evolution than emotions, and the mechanisms underlying the processing of conspecific vocalizations do not directly generalize to cross-species vocalizations. Consequently, decoding social messages from vocalizations may rely less on universal rules than previously thought.

Similar content being viewed by others

Event-related potentials indicate differential neural reactivity to species and valence information in vocal stimuli in sleeping dogs

Article
Open access
04 September 2023

Species-independent analysis and identification of emotional animal vocalizations

Article
Open access
06 August 2025

Sound symbolism facilitates interspecies communication between humans and domestic dogs (Canis familiaris)

Article
Open access
11 November 2025

Data availability

All raw data is available in the Supplementary Materials. An example of the Praat script used to assemble the playback sequences and the R script used for the statistical analysis can be found in the Supplementary Materials too.

References

  1. Guilford, T. & Dawkins, M. S. Receiver psychology and the evolution of animal signals. Anim. Behav. 42, 1–14 (1991).

    Google Scholar 

  2. Miller, C. T. & Bee, M. A. Receiver psychology turns 20: Is it time for a broader approach?. Anim. Behav. 83, 331–343 (2012).

    Google Scholar 

  3. Krebs, J. R. & Dawkins, R. Animal signals: mind-reading and manipulation. in Behavioural Ecology: an evolutionary approach 380–402Blackwell Sci. Publ., (1984).

  4. Fitch, W. T. & Hauser, M. D. Unpacking “honesty”:Vertebrate vocal production and the evolution of acoustic signals In (eds Simmons, A. M. et al.) (2003).

  5. Charlton, B. D., Pisanski, K., Raine, J. & Reby, D. Coding of Static Information in Terrestrial Mammal Vocal Signals. in Coding Strategies in Vertebrate Acoustic Communication (eds Aubin, T. & Mathevon, N.) 115–136 (Springer International Publishing, doi:https://doi.org/10.1007/978-3-030-39200-0_5. (2020).

  6. Briefer, E. F. Coding for ‘Dynamic’ Information: Vocal Expression of Emotional Arousal and Valence in Non-human Animals. in Coding Strategies in Vertebrate Acoustic Communication (eds Aubin, T. & Mathevon, N.) 137–162 (Springer International Publishing, doi:https://doi.org/10.1007/978-3-030-39200-0_6. (2020).

  7. Nesse, R. M. Evolutionary explanations of emotions. Hum. Nat. 1, 261–289 (1990).

    Google Scholar 

  8. Mendl, M. T., Burman, O. H. P. & Paul, E. S. An integrative and functional framework for the study of animal emotion and mood. Proceedings of the Royal Society B: Biological Sciences https://doi.org/10.1098/rspb.2010.0303 (2010).

    Google Scholar 

  9. Kleinginna, P. R. & Kleinginna, A. M. A categorized list of motivation definitions, with a suggestios for a consensual definition. Motiv. Emot. 5, 263–291 (1981).

    Google Scholar 

  10. Morton, E. S. On the occurrence and significance of motivation – structural rules in some bird and mammal sounds. Am. Nat. 111, 855–869 (1977).

    Google Scholar 

  11. August, P. V. & Anderson, J. G. T. Mammal sounds and motivation-structural rules: A test of the hypothesis. J. Mammal. 68, 1–9 (1987).

    Google Scholar 

  12. Gygax, L. Wanting, liking and welfare: The role of affective states in proximate control of behaviour in vertebrates. Ethology 123, 689–704 (2017).

    Google Scholar 

  13. Taylor, A. M. & Reby, D. The contribution of source-filter theory to mammal vocal communication research. J. Zool. 280, 221–236 (2010).

    Google Scholar 

  14. Fournier, F., Briefer, E. F., Pisanski, K. & Levréro, F. What do we know about vocal communication of emotion between different species of terrestrial tetrapods? Biol Rev 4, (2026).

  15. Andics, A. & Faragó, T. Voice perception across species. in Oxford Handbook of Voice Perception (eds Frühholz, S. & Belin, P.) 362–392 (Oxford University Press, doi:https://doi.org/10.1093/oxfordhb/9780198743187.013.16. (2019).

  16. Faragó, T. et al. Humans rely on the same rules to assess emotional valence and intensity in conspecific and dog vocalizations. Biol. Lett. 10, 20130926 (2014).

    Google Scholar 

  17. Pongrácz, P., Molnár, C., Miklósi, Á. & Csányi, V. Human listeners are able to classify dog (Canis familiaris) barks recorded in different situations. J. Comp. Psychol. 119, 136–144 (2005).

    Google Scholar 

  18. Faragó, T., Takács, N., Miklósi, Á. & Pongrácz, P. Dog growls express various contextual and affective content for human listeners. R. Soc. Open Sci 4, 170134 (2017).

    Google Scholar 

  19. Maruščáková, I. L. et al. Humans (Homo sapiens) judge the emotional content of piglet (Sus scrofa domestica) calls based on simple acoustic parameters, not personality, empathy, nor attitude toward animals. J. Comp. Psychol. 129, 121–131 (2015).

    Google Scholar 

  20. Kamiloğlu, R. G., Slocombe, K. E., Haun, D. B. M. & Sauter, D. A. Human listeners’ perception of behavioural context and core affect dimensions in chimpanzee vocalizations. Proc. R. Soc. B Biol. Sci. 287, 20201148 (2020).

    Google Scholar 

  21. Debracque, C., Slocombe, K. E., Clay, Z., Grandjean, D. & Gruber, T. Humans recognize affective cues in primate vocalizations: Acoustic and phylogenetic perspectives. Sci. Rep. 13, 10900 (2023).

    Google Scholar 

  22. Merkies, K., Crouchman, E. & Belliveau, H. Human ability to determine affective states in domestic horse whinnies. Anthrozoos 0, 1–12 (2021).

    Google Scholar 

  23. Sowerby Greenall, J., Cornu, L., Maigrot, A.-L., De La Torre, M. P. & Briefer, E. F. Age, empathy, familiarity, domestication and call features enhance human perception of animal emotion expressions. R. Soc. Open Sci. https://doi.org/10.1098/rsos.221138 (2022).

    Google Scholar 

  24. Huber, A., Barber, A. L. A., Faragó, T., Müller, C. A. & Huber, L. Investigating emotional contagion in dogs (Canis familiaris) to emotional sounds of humans and conspecifics. Anim. Cogn. 20, 703–715 (2017).

    Google Scholar 

  25. Maigrot, A.-L., Hillmann, E. & Briefer, E. F. Cross-species discrimination of vocal expression of emotional valence by Equidae and Suidae. BMC Biol. 20, 1–14 (2022).

    Google Scholar 

  26. Smith, A. V. et al. Domestic horses (Equus caballus) discriminate between negative and positive human nonverbal vocalisations. Sci. Rep. 8, 1–8 (2018).

    Google Scholar 

  27. Scheumann, M., Hasting, A. S., Zimmermann, E. & Kotz, S. A. Human novelty response to emotional animal vocalizations: Effects of phylogeny and familiarity. Front. Behav. Neurosci. https://doi.org/10.3389/fnbeh.2017.00204 (2017).

    Google Scholar 

  28. Scheumann, M., Hasting, A. S., Kotz, S. A. & Zimmermann, E. The voice of emotion across species: How do human listeners recognize animals’ affective states?. PLoS One 9, e91192 (2014).

    Google Scholar 

  29. Compton, L. A., Clarke, J. A., Seidensticker, J. & Ingrisano, D. R. Acoustic characteristics of white-nosed coati vocalizations: A test of motivation-structural rules. J. Mammal. 82, 1054–1058 (2001).

    Google Scholar 

  30. Hollén, L. I. & Manser, M. B. Motivation before meaning: Motivational information encoded in meerkat alarm calls develops earlier than referential information. Am. Nat. 169, 758–767 (2007).

    Google Scholar 

  31. Kong, X. et al. Behavioral-psychological motivations encoded in the vocal repertoire of captive Amur tiger (Panthera tigris altaica) cubs. BMC Zool. 7, 2 (2022).

    Google Scholar 

  32. Robbins, R. L. & McCreery, E. K. African wild dog pup vocalizations with special reference to Morton’s model. Behaviour 140, 333–351 (2003).

    Google Scholar 

  33. Kitchen, D. M., da Cunha, R. G. T., Holzmann, I. & de Oliveira, D. A. G. Function of Loud Calls in Howler Monkeys. in Howler Monkeys 369–399Springer New York, (2015). https://doi.org/10.1007/978-1-4939-1957-4_14

  34. Leuchtenberger, C., Sousa-Lima, R., Duplaix, N., Magnusson, W. E. & Mourão, G. Vocal repertoire of the social giant otter. J. Acoust. Soc. Am. 136, 2861 (2014).

    Google Scholar 

  35. Dunlop, R. A. Potential motivational information encoded within humpback whale non-song vocal sounds. J. Acoust. Soc. Am. 141, 2204–2213 (2017).

    Google Scholar 

  36. Cusano, D. A., Indeck, K. L., Noad, M. J. & Dunlop, R. A. Humpback whale (Megaptera novaeangliae) social call production reflects both motivational state and arousal. Bioacoustics 00, 1–24 (2020).

    Google Scholar 

  37. Clement, M. J. & Kanwal, J. S. Simple syllabic calls accompany discrete behavior patterns in captive Pteronotus parnellii: An illustration of the motivation-structure hypothesis. Sci. World J. (2012). (2012).

  38. Pitcher, B. J., Briefer, E. F., Vannoni, E. & McElligott, A. G. Fallow bucks attend to vocal cues of motivation and fatigue. Behav. Ecol. 25, 392–401 (2014).

    Google Scholar 

  39. Demartsev, V. et al. Harsh vocal elements affect counter-singing dynamics in male rock hyrax. Behav. Ecol. 27, 1397–1404 (2016).

    Google Scholar 

  40. Lingle, S. & Riede, T. Deer mothers are sensitive to infant distress vocalizations of diverse mammalian species. Am. Nat. 184, 510–522 (2014).

    Google Scholar 

  41. Lingle, S., Wyman, M. T., Kotrba, R., Teichroeb, L. J. & Romanow, C. A. What makes a cry a cry? A review of infant distress vocalizations. Curr. Zool. 58, 698–726 (2012).

    Google Scholar 

  42. Marx, A. et al. Occurrences of non-linear phenomena and vocal harshness in dog whines as indicators of stress and ageing. Sci. Rep. 11, 4468 (2021).

    Google Scholar 

  43. Faragó, T., Pongrácz, P., Range, F., Virányi, Z. & Miklósi, Á. The bone is mine’: Affective and referential aspects of dog growls. Anim. Behav. 79, 917–925 (2010).

    Google Scholar 

  44. Faragó, T. et al. Dogs’ expectation about signalers’ body size by virtue of their growls. PLoS One 5, e15175 (2010).

    Google Scholar 

  45. Bálint, A., Faragó, T., Dóka, A., Miklósi, Á. & Pongrácz, P. ‘Beware, I am big and non-dangerous!’ – Playfully growling dogs are perceived larger than their actual size by their canine audience. Appl. Anim. Behav. Sci. 148, 128–137 (2013).

    Google Scholar 

  46. Anikin, A. & Persson, T. Nonlinguistic vocalizations from online amateur videos for emotion research: A validated corpus. Behav. Res. Methods. 49, 758–771 (2017).

    Google Scholar 

  47. Livingstone, S. R. & Russo, F. A. The ryerson audio-visual database of emotional speech and song (ravdess): A dynamic, multimodal set of facial and vocal expressions in north American english. PLoS ONE https://doi.org/10.1371/journal.pone.0196391 (2018).

    Google Scholar 

  48. Plooij, F. X., Van De Rijt-Plooij, H., Fischer, M., Wilson, M. L. & Pusey, A. An archive of longitudinal recordings of the vocalizations of adult Gombe chimpanzees. Sci. Data 2, 1–7 (2015).

    Google Scholar 

  49. Miklósi, Á. & Topál, J. What does it take to become ‘best friends’? Evolutionary changes in canine social competence. Trends Cogn. Sci. 17, 287–94 (2013).

    Google Scholar 

  50. Cuaya, L. V., Hernández-Pérez, R., Boros, M., Deme, A. & Andics, A. Speech naturalness detection and language representation in the dog brain. Neuroimage 248, 118811 (2022).

    Google Scholar 

  51. Andics, A. et al. Neural mechanisms for lexical processing in dogs. Science 353, 1030–1032 (2016).

    Google Scholar 

  52. Gergely, A. et al. Dog brains are sensitive to infant- and dog-directed prosody. Commun. Biol. 6, 859 (2023).

    Google Scholar 

  53. Jahn-Eimermacher, A., Lasarzik, I. & Raber, J. Statistical analysis of latency outcomes in behavioral experiments. Behav. Brain Res. 221, 271–275 (2011).

    Google Scholar 

  54. Quervel-Chaumette, M., Faerber, V., Faragó, T., Marshall-Pescini, S. & Range, F. Investigating empathy-like responding to conspecifics’ distress in pet dogs. PLoS One 11, e0152920 (2016).

    Google Scholar 

  55. Ehret, G. & Haack, B. Motivation and arousal influence sound-induced maternal pup‐retrieving behavior in lactating house mice. Z. Tierpsychol 65, 25–39 (1984).

    Google Scholar 

  56. Andics, A., Gácsi, M., Faragó, T., Kis, A. & Miklósi, Á. Voice-sensitive regions in the dog and human brain are revealed by comparative FMRI. Curr. Biol. 24, 574–578 (2014).

    Google Scholar 

  57. Cools, A. K. A., Van Hout, A.-M. & Nelissen, M. H. J. Canine reconciliation and third-party-initiated postconflict affiliation: Do peacemaking social mechanisms in dogs rival those of higher primates?. Ethology 114, 53–63 (2008).

    Google Scholar 

  58. Mason, P. Lessons from helping behavior in rats. Curr. Opin. Neurobiol. 68, 52–56 (2021).

    Google Scholar 

  59. Thuppil, V. & Coss, R. G. Wild Asian elephants distinguish aggressive tiger and leopard growls according to perceived danger. Biol. Lett. 9, 20130518 (2013).

    Google Scholar 

  60. Thévenet, J. et al. Crocodile perception of distress in hominid baby cries. Proc. R. Soc. B Biol. Sci. 290, (2023).

  61. Szameitat, D. P. et al. Differentiation of emotions in laughter at the behavioral level. Emotion 9, 397–405 (2009).

    Google Scholar 

  62. Radford, A. N., Morris-Drake, A. & Arbon, J. J. After the fight: post-contest acoustic signalling. Proceedings of the Royal Society B: Biological Sciences 292, 0–3 (2025).

    Google Scholar 

  63. Mouterde, S. C. et al. Triumph displays inform eavesdropping little blue penguins of new dominance asymmetries. Anim. Behav. 83, 605–611 (2012).

    Google Scholar 

  64. Lord, K. A., Feinstein, M. & Coppinger, R. P. Barking and mobbing. Behav. Processes 81, 358–68 (2009).

    Google Scholar 

  65. Zimmermann, E., Leliveld, L. M. C. & Schehka, S. Toward the evolutionary roots of affective prosody in human acoustic communication: A comparative approach to mammalian voices. in Evolution of Emotional Communication: from Sounds in Nonhuman Mammals to Speech and Music in Man. (eds Altenmüller, E., Schmidt, S. & Zimmermann, E.) 116–132 (Oxford University Press, (2013).

  66. Briefer, E. F. Vocal expression of emotions in mammals: Mechanisms of production and evidence. J. Zool. 288, 1–20 (2012).

    Google Scholar 

  67. Huang, X. et al. Acoustic similarity elicits responses to heterospecific distress calls in bats (Mammalia: Chiroptera). Anim. Behav. 146, 143–154 (2018).

    Google Scholar 

  68. Quaranta, A., D’ingeo, S., Amoruso, R. & Siniscalchi, M. Emotion recognition in cats. Animals 10, 1–13 (2020).

    Google Scholar 

  69. Mason, M. A., Semple, S., Marshall, H. H. & McElligott, A. G. Goats discriminate emotional valence in the human voice. Anim. Behav. 209, 227–240 (2024).

    Google Scholar 

  70. Lehoczki, F., Pérez Fraga, P. & Andics, A. Family pigs’ and dogs’ reactions to human emotional vocalizations: A citizen science study. Anim. Behav. 214, 207–218 (2024).

    Google Scholar 

  71. Vitousek, M. N., Adelman, J. S., Gregory, N. C. & St. Clair, J. J. H. Heterospecific alarm call recognition in a non-vocal reptile. Biol. Lett. 3, 632–4 (2007).

    Google Scholar 

  72. Müller, C. A. & Manser, M. B. The information banded mongooses extract from heterospecific alarms. Anim. Behav. 75, 897–904 (2008).

    Google Scholar 

  73. Fichtel, C. Reciprocal recognition of sifaka (Propithecus verreauxi verreauxi) and redfronted lemur (Eulemur fulvus rufus) alarm calls. Anim. Cogn. 7, 45–52 (2004).

    Google Scholar 

  74. Müller, C. A., Schmitt, K., Barber, A. L. A. & Huber, L. Dogs can discriminate emotional expressions of human faces. Curr. Biol. 25, 601–605 (2015).

    Google Scholar 

  75. Turcsán, B., Szánthó, F., Miklósi, Á. & Kubinyi, E. Fetching what the owner prefers? Dogs recognize disgust and happiness in human behaviour. Anim. Cogn. 18, 83–94 (2015).

    Google Scholar 

  76. Plutchik, R. Individual and breed differences in approach and withdrawal in dogs. Behaviour 40, 302–311 (1971).

    Google Scholar 

  77. Trefry, S. A. & Hik, D. S. Eavesdropping on the neighbourhood: Collared pika (Ochotona collaris) responses to playback calls of conspecifics and heterospecifics. Ethology 115, 928–938 (2009).

    Google Scholar 

  78. Herbinger, I., Papworth, S., Boesch, C. & Zuberbühler, K. Vocal, gestural and locomotor responses of wild chimpanzees to familiar and unfamiliar intruders: A playback study. Anim. Behav. 78, 1389–1396 (2009).

    Google Scholar 

  79. Pfannerstill, V., Balkenhol, N., Bennitt, E., Maboga, O. S. & Scheumann, M. Assessing the potential of conspecific playbacks as a post-translocation management tool for white rhinoceros. Conservation Science and Practice https://doi.org/10.1111/csp2.12996 (2023).

    Google Scholar 

  80. Fuller, J. L. & Cords, M. Versatility in a loud call: Dual affiliative and agonistic functions in the blue monkey boom. Ethology 126, 10–23 (2020).

    Google Scholar 

  81. Scandurra, A., Alterisio, A., Di Cosmo, A. & D’Aniello, B. Behavioral and perceptual differences between sexes in dogs: An overview. Animals 8, 151 (2018).

    Google Scholar 

  82. Müller, C. A., Mayer, C., Dörrenberg, S., Huber, L. & Range, F. Female but not male dogs respond to a size constancy violation. Biol. Lett. rsbl.2011.0287-. https://doi.org/10.1098/rsbl.2011.0287 (2011).

    Google Scholar 

  83. D’Aniello, B. et al. Sex differences in the behavioral responses of dogs exposed to human chemosignals of fear and happiness. Anim. Cogn. 24, 299–309 (2021).

    Google Scholar 

  84. Persson, M. E., Roth, L. S. V., Johnsson, M., Wright, D. & Jensen, P. Human-directed social behaviour in dogs shows significant heritability. Genes, Brain Behav. n/a-n/a (2014). https://doi.org/10.1111/gbb.12194

  85. Hamann, S. & Canli, T. Individual differences in emotion processing. Curr. Opin. Neurobiol. 14, 233–238 (2004).

    Google Scholar 

  86. Lonsdorf, E. V. et al. Boys will be boys: Sex differences in wild infant chimpanzee social interactions. Anim. Behav. 88, 79–83 (2014).

    Google Scholar 

  87. Reed, A. E. & Carstensen, L. L. The theory behind the age-related positivity effect. Front. Psychol. 3, 1–9 (2012).

    Google Scholar 

  88. Mather, M. & Carstensen, L. L. Aging and motivated cognition: The positivity effect in attention and memory. Trends Cogn. Sci. 9, 496–502 (2005).

    Google Scholar 

  89. Smit, I., Szabó, D. & Kubinyi, E. Age-related positivity effect on behavioural responses of dogs to human vocalisations. Sci. Rep. 9, 20201 (2019).

    Google Scholar 

  90. Turcsán, B. et al. Individual and group level personality change across the lifespan in dogs. Sci. Rep. 10, 17276 (2020).

    Google Scholar 

  91. Merola, I., Prato-Previde, E. & Marshall-Pescini, S. Social referencing in dog-owner dyads?. Anim. Cogn. https://doi.org/10.1007/s10071-011-0443-0 (2011).

    Google Scholar 

  92. Mongillo, P. et al. Does the attachment system towards owners change in aged dogs?. Physiol. Behav. 120, 64–69 (2013).

    Google Scholar 

  93. Gácsi, M., Maros, K., Sernkvist, S., Faragó, T. & Miklósi, Á. Human analogue safe haven effect of the owner: Behavioural and heart rate response to stressful social stimuli in dogs. PLoS One 8, e58475 (2013).

    Google Scholar 

  94. Bekoff, M. Social communication in canids: Evidence for the evolution of a stereotyped mammalian display. Science 197, 1097–1099 (1977).

    Google Scholar 

  95. Filippi, P. et al. Humans recognize emotional arousal in vocalizations across all classes of terrestrial vertebrates: Evidence for acoustic universals. Proc. R. Soc. B Biol. Sci. 284, 20170990 (2017).

    Google Scholar 

  96. Filippi, P., Gogoleva, S. S., Volodina, E. V., Volodin, I. A. & Boer, B. Humans identify negative (but not positive) arousal in silver fox vocalizations: Implications for the adaptive value of interspecific eavesdropping. Curr. Zool. 63, 445–456 (2017).

    Google Scholar 

  97. Manser, M. B., Bell, M. B. V. & Fletcher, L. B. The information that receivers extract from alarm calls in suricates. Proceedings of the Royal Society of London. Series B: Biological Sciences 268, 2485–91 (2001).

    Google Scholar 

  98. Pongrácz, P., Lenkei, R., Marx, A. & Faragó, T. Should i whine or should i bark? Qualitative and quantitative differences between the vocalizations of dogs with and without separation-related symptoms. Appl. Anim. Behav. Sci. 196, 61–68 (2017).

    Google Scholar 

  99. Volodina, E. V., Volodin, I. A. & Filatova, O. A. The Occurence Of Nonlinear Vocal Phenomena In Frustration Whines Of The Domestic Dog (Canis Familiaris). Adv. Bioacoustics 2. 47, 245–255 (2006).

    Google Scholar 

  100. Volsche, S. et al. Dogs produce distinctive play pants: Confirming Simonet. Int. J. Comp. Psychol. 35, 0–15 (2022).

    Google Scholar 

  101. Simonet, P., Versteeg, D. & Storie, D. Dog-laughter: Recorded playback reduces stress related behavior in shelter dogs. in Proceedings of the 7thInternational Conference on Environmental Enrichment (2005).

  102. Lehoczki, F., Szenczi, P., Bánszegi, O., Lakatos, K. & Faragó, T. Cross-species effect of separation calls: Family dogs’ reactions to pup, baby, kitten and artificial sounds. Anim. Behav. 168, 169–185 (2020).

    Google Scholar 

  103. Custance, D. M. & Mayer, J. Empathic-like responding by domestic dogs (Canis familiaris) to distress in humans: An exploratory study. Anim. Cogn. 15, 851–9 (2012).

    Google Scholar 

  104. Reddy, R. B. & Sandel, A. A. Social relationships between chimpanzee sons and mothers endure but change during adolescence and adulthood. Behav. Ecol. Sociobiol. https://doi.org/10.1007/s00265-020-02937-7 (2020).

    Google Scholar 

  105. Raine, J., Pisanski, K., Bond, R., Simner, J. & Reby, D. Human roars communicate upper-body strength more effectively than do screams or aggressive and distressed speech. PLoS One 14, e0213034 (2019).

    Google Scholar 

  106. Raine, J., Pisanski, K., Oleszkiewicz, A., Simner, J. & Reby, D. Human listeners can accurately judge strength and height relative to self from aggressive roars and speech. iScience 4, 273–280 (2018).

    Google Scholar 

  107. Kamiloğlu, R. G., Çalışkan, C., Slocombe, K. E. & Sauter, D. A. Threat vocalisations are acoustically similar between humans (Homo sapiens) and chimpanzees (Pan troglodytes). Bioacoustics 00, 1–14 (2023).

    Google Scholar 

  108. Crockford, C. & Boesch, C. Context-specific calls in wild chimpanzees, Pan troglodytes verus: Analysis of barks. Anim. Behav. 66, 115–125 (2003).

    Google Scholar 

  109. Winkler, S. L. & Bryant, G. A. Play vocalisations and human laughter: A comparative review. Bioacoustics 30, 499–526 (2021).

    Google Scholar 

  110. Davila-Ross, M., Owren, M. J. & Zimmermann, E. Reconstructing the evolution of laughter in great apes and humans. Curr. Biol. 19, 1106–1111 (2009).

    Google Scholar 

  111. Matsusaka, T. When does play panting occur during social play in wild chimpanzees? Primates 45, 221–229 (2004).

    Google Scholar 

  112. Davila-Ross, M., Allcock, B., Thomas, C. & Bard, K. A. Aping expressions? Chimpanzees produce distinct laugh types when responding to laughter of others. Emotion 11, 1013–1020 (2011).

    Google Scholar 

  113. Core Team, R. C. T. R. R: A language and environment for statistical computing. at (2017).

  114. RStudio_Team. RStudio: Integrated Development Environment for R. at. (2015).

Download references

Acknowledgements

The authors are grateful to the owners for participating in our tests and incredibly thankful to Théo Lemeux for the blind coding of the videos for the reliability analysis.

Funding

Open access funding provided by Eötvös Loránd University. TF was supported by The Hungarian Academy of Sciences via the János Bolyai Research Scholarship (BO/751/20), The European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (950159) and the Horizon Europe research and innovation programme (101125731), The Ministry for Innovation and Technology from the source of the National Research, Development and Innovation Fund via the New National Excellence Program (ÚNKP-20-5-ELTE-337, 21-5-ELTE-1061 and ÚNKP-22-5-ELTE-475). PP was supported by the EKÖP-25-4-II University Excellence Scholarship Program by the National Research, Development and Innovation Office. (EKÖP-25-4-II-ELTE-900). EK was supported by The Hungarian Academy of Sciences via a grant to the MTA-ELTE ‘Lendület/Momentum’ Companion Animal Research Group (grant no. PH1404/21) and The Hungarian Academy of Sciences via the National Brain Programme 3.0 (NAP2022-I-3/2022). AA was supported by The Hungarian Academy of Sciences via the National Brain Programme 3.0 (NAP2022-I-3/2022) and The European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (950159). This work was also supported by the European Union’s Horizon Europe Framework programme under the Marie Skłodowska-Curie Grant Agreement No 101168998 (VoCS project).

Author information

Author notes

  1. Joint Senior Authors: Enikő Kubinyi and Attila Andics.

Authors and Affiliations

  1. Neuroethology of Communication Lab, Department of Ethology, Eötvös Loránd University, Budapest, Hungary

    Tamás Faragó, Beatrix Laczi, Paula Pérez Fraga & Attila Andics

  2. BARKS Lab, Department of Ethology, Eötvös Loránd University, Budapest, Hungary

    Tamás Faragó & Paula Pérez Fraga

  3. Department of Ethology, ELTE Eötvös Loránd University, Budapest, Hungary

    Lilla Kocsis, Beatrix Laczi, Irene Rojas Atares, Morgane Audiguier & Soufiane Bel Rhali

  4. Department of Psychology, University of York, York, UK

    Katie E. Slocombe

  5. MTA-ELTE Lendület “Momentum” Companion Animal Research Group, Budapest, Hungary

    Enikő Kubinyi

  6. ELTE NAP Canine Brain Research Group, Budapest, Hungary

    Enikő Kubinyi & Attila Andics

Authors

  1. Tamás Faragó
    View author publications

    Search author on:PubMed Google Scholar

  2. Lilla Kocsis
    View author publications

    Search author on:PubMed Google Scholar

  3. Beatrix Laczi
    View author publications

    Search author on:PubMed Google Scholar

  4. Irene Rojas Atares
    View author publications

    Search author on:PubMed Google Scholar

  5. Paula Pérez Fraga
    View author publications

    Search author on:PubMed Google Scholar

  6. Morgane Audiguier
    View author publications

    Search author on:PubMed Google Scholar

  7. Soufiane Bel Rhali
    View author publications

    Search author on:PubMed Google Scholar

  8. Katie E. Slocombe
    View author publications

    Search author on:PubMed Google Scholar

  9. Enikő Kubinyi
    View author publications

    Search author on:PubMed Google Scholar

  10. Attila Andics
    View author publications

    Search author on:PubMed Google Scholar

Contributions

Conceptualization: TFMethodology: TF, PPF, KES, AAInvestigation: TF, LK, BL, IRA, PPF, MA, SBRValidation: TF, LK, SBRAnalysis: TF, LK, IRA, MA, SBRVisualization: TFSupervision: TF, EK, AAWriting—original draft: TF, LK, AAWriting—review & editing: TF, LK, IRA, PPF, MA, SBR, KES, EK, AAFunding: TF, EK, AA.

Corresponding author

Correspondence to
Tamás Faragó.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

The authors declare that they have no competing interests. The authors confirm that the sound material used in the study was either their own recordings (dog vocalizations were recorded by FT, chimpanzee vocalizations were recorded by KES) or was from freely available resources under CC BY-NC-SA 4.0 licence (human calls were from Andrey Anikin’s 2017 corpus: https://cogsci.se/publications/2017_corpus.html, and human speech from the RAVDESS corpus: https://www.kaggle.com/datasets/uwrfkaggler/ravdess-emotional-speech-audio), thus no permissions were needed to use them in our study.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary Material 1 (download CSV )

Supplementary Material 2

Supplementary Material 3 (download PDF )

Supplementary Material 4

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and permissions

About this article

Cite this article

Faragó, T., Kocsis, L., Laczi, B. et al. Dogs’ reactions to motivations and emotions in conspecific and heterospecific vocalizations.
Sci Rep (2026). https://doi.org/10.1038/s41598-026-46906-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41598-026-46906-y

Source: Ecology - nature.com

Otolith shape and microchemistry reveal fine-scale population connectivity in the myctophid Benthosema glaciale (Reinhardt, 1837) along a complex seascape

Prevalence of Pseudomonas aeruginosa in Australian wild birds, native wildlife, livestock and domestic animals

This portal is not a newspaper as it is updated without periodicity. It cannot be considered an editorial product pursuant to law n. 62 of 7.03.2001. The author of the portal is not responsible for the content of comments to posts, the content of the linked sites. Some texts or images included in this portal are taken from the internet and, therefore, considered to be in the public domain; if their publication is violated, the copyright will be promptly communicated via e-mail. They will be immediately removed.

Back to Top
Close