This paper investigates the use of heterogeneous speech corpora for automatic assessment of personality traits in terms of the Big-Five 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 Sub-challenge, 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.

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Computational paralinguistics,Automatic personality assessment,OCEAN,Cross-lingual,Cross-age

• Mathematics - Natural Sciences
• Computer and Information Sciences - Natural Sciences