This paper reports preliminary experiments on automatic attribution of personality traits based on nonverbal vocal behavioral cues. In particular, the work shows how prosodic features can be used to predict, with an accuracy up to 75% depending on the trait, the personality assessments performed by human judges on a collection of 640 speech samples. The assessments are based on a short version of the Big Five Inventory, one of the most widely used ques- tionnaires for personality assessment. The judges did not understand the language spoken in the speech samples so that the influence of the verbal content is limited. To the best of our knowledge, this is the first work aimed at infer- ring automatically traits attributed by judges rather than traits self-reported by subjects.