Integrating voice recognition into models of person perception

The results of one empirical study are presented to investigate whether voice recognition might profitably be integrated into a single IAC network for person perception. An identity priming paradigm was used to determine whether face perception and voice perception combined to influence one another. The results revealed within-modality priming of faces by prior presentations of faces, and of voices by prior presentation of voices. Critically, cross-modality priming was also revealed, confirming that the two modalities can be represented within a single system and can influence one another. These results are supported by the results of a simulation, and are discussed in terms of the theoretical development of IAC, and the benefits and future questions that arise from consideration of an integrated multimodal model of person perception.