Highly accurate and robust identity perception from personally familiar voices

Abstract

Previous research suggests that familiarity with a voice can afford benefits for voice and speech perception. However, even familiar voice perception has been reported to be error-prone in previous research, especially in the face of challenges such as reduced verbal cues and acoustic distortions. It has been hypothesised that such findings may arise due to listeners not being “familiar enough” with the voices used in laboratory studies, and thus being inexperienced with their full vocal repertoire. By extension, voice perception based on highly familiar voices – acquired via substantial, naturalistic experience – should therefore be more robust than voice perception from less familiar voices. We investigated this proposal by contrasting voice perception of personally-familiar voices (participants’ romantic partners) versus lab-trained voices in challenging experimental tasks. Specifically, we tested how differences in familiarity may affect voice identity perception from non-verbal vocalisations and acoustically-modulated speech. Large benefits for the personally-familiar voice over less familiar, lab-trained voice were found for identity recognition, with listeners displaying both highly accurate yet more conservative recognition of personally familiar voices. However, no familiar-voice benefits were found for speech comprehension against background noise. Our findings suggest that listeners have fine-tuned representations of highly familiar voices that result in more robust and accurate voice recognition despite challenging listening contexts, yet these advantages may not always extend to speech perception. Our study therefore highlights that familiarity is indeed a continuum, with identity perception for personally-familiar voices being highly accurate

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