A lion's roar, a dog's bark, an angry yell in a pub brawl: what do these vocalizations have in common? They all sound harsh due to nonlinear vocal phenomena (NLP)—deviations from regular voice production, hypothesized to lower perceived voice pitch and thereby exaggerate the apparent body size of the vocalizer. To test this yet uncorroborated hypothesis, we synthesized human nonverbal vocalizations, such as roars, groans and screams, with and without NLP (amplitude modulation, subharmonics and chaos). We then measured their effects on nearly 700 listeners' perceptions of three psychoacoustic (pitch, timbre, roughness) and three ecological (body size, formidability, aggression) characteristics. In an explicit rating task, all NLP lowered perceived voice pitch, increased voice darkness and roughness, and caused vocalizers to sound larger, more formidable and more aggressive. Key results were replicated in an implicit associations test, suggesting that the ‘harsh is large’ bias will arise in ecologically relevant confrontational contexts that involve a rapid, and largely implicit, evaluation of the opponent's size. In sum, nonlinearities in human vocalizations can flexibly communicate both formidability and intention to attack, suggesting they are not a mere byproduct of loud vocalizing, but rather an informative acoustic signal well suited for intimidating potential opponents.
Development and validation of the Alcohol Identity Implicit Associations Test (AI-IAT)