In this paper, we present ongoing experiments and insights regarding automatic and human assessment of perceived personality. While within the INTERSPEECH Speaker Trait Challenge participants will train systems in order to recognize binary targets along the Big 5 personality trait, we will analyze and discuss properties of the data, the labeling scheme and the predictive quality. Conducting factor analyses, estimating reliability, and building regression models capturing dimensions of personality we compare all results to our own work and introduce a new extension of our personality database. In conclusion, this paper contributes in methodology and understanding on how to asses the perceived personality from an unknown speaker by humans and machines. Index Terms: extra-linguistic speech properties, personality modeling from speech, speaker characteristics