Acoustic-Prosodic Automatic Personality Trait Assessment for Adults and Children

This paper investigates the use of heterogeneous speech corpora for automatic assessment of personality traits in terms of the BigFive OCEAN dimensions. The motivation for this work is twofold: the need to develop methods to overcome the lack of children’s speech corpora, particularly severe when targeting personality traits, and the interest on cross-age comparisons of acoustic-prosodic features to build robust paralinguistic detectors. For this purpose, we devise an experimental setup with age mismatch utilizing the Interspeech 2012 Personality Subchallenge, containing adult speech, as training data. As test data, we use a corpus of children’s European Portuguese speech. We investigate various features sets such as the Sub-challenge baseline features, the recently introduced eGeMAPS features and our own knowledge-based features. The preliminary results bring insights into cross-age and -language detection of personality traits in spontaneous speech, pointing out to a stable set of acoustic-prosodic features for Extraversion and Agreeableness in both adult and child speech.