Matching Voice and Face Identity From Static Images

Previous research has suggested that people are unable to correctly choose which unfamiliar voice and static image of a face belong to the same person. Here, we present evidence that people can perform this task with greater than chance accuracy. In Experiment 1, participants saw photographs of two, same-gender models, while simultaneously listening to a voice recording of one of the models pictured in the photographs and chose which of the two faces they thought belonged to the same model as the recorded voice. We included three conditions: (a) the visual stimuli were frontal headshots (including the neck and shoulders) and the auditory stimuli were recordings of spoken sentences; (b) the visual stimuli only contained cropped faces and the auditory stimuli were full sentences; (c) we used the same pictures as Condition 1 but the auditory stimuli were recordings of a single word. In Experiment 2, participants performed the same task as in Condition 1 of Experiment 1 but with the stimuli presented in sequence. Participants also rated the model's faces and voices along multiple physical dimensions (e.g., weight,) or personality dimensions (e.g., extroversion); the degree of agreement between the ratings for each model's face and voice was compared to performance for that model in the matching task. In all three conditions, we found that participants chose, at better than chance levels, which faces and voices belonged to the same person. Performance in the matching task was not correlated with the degree of agreement on any of the rated dimensions.