How many voices did you hear? Natural variability disrupts identity perception in unfamiliar listeners

Within-person variability is a striking feature of human voices: our voices sound different depending on the context (laughing vs. talking to a child vs. giving a speech). When perceiving speaker identities, listeners therefore need to not only "tell people apart" (perceiving exemplars from two different speakers as separate identities) but also "tell people together" (perceiving different exemplars from the same speaker as a single identity). In the current study, we investigated how such natural within-person variability affects voice identity perception. Using voices from a popular TV show, listeners, who were either familiar or unfamiliar with the show, sorted naturally-varying voice clips from 2 speakers into clusters to represent perceived identities. Across three independent participant samples, unfamiliar listeners perceived more identities than familiar listeners and frequently mistook exemplars from the same speaker to be different identities. These findings point towards a selective failure in "telling people together". Our study highlights within-person variability as a key feature of voices that has striking effects on (unfamiliar) voice identity perception. Our findings not only open up a new line of enquiry in the field of voice perception but also call for a re-evaluation of theoretical models to account for natural variability during identity perception.