Acoustic-Prosodic Automatic Personality Trait Assessment for Adults and Children

  • Rubén Solera-UreñaEmail author
  • Helena Moniz
  • Fernando Batista
  • Ramón F. Astudillo
  • Joana Campos
  • Ana Paiva
  • Isabel Trancoso
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10077)


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.


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



Work supported by national funds through Fundação para a Ciência e a Tecnologia (FCT) with reference UID/CEC/50021/2013, under Post-doc grant SFRH/PBD/95849/2013, by project CMUP-ERI/HCI/0051/2013 (INSIDE), and by project H2020-EU.3.7 contract 653587 (LAW-TRAIN).


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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Rubén Solera-Ureña
    • 1
    Email author
  • Helena Moniz
    • 1
    • 2
  • Fernando Batista
    • 1
    • 3
  • Ramón F. Astudillo
    • 1
    • 4
  • Joana Campos
    • 5
    • 6
  • Ana Paiva
    • 5
    • 6
  • Isabel Trancoso
    • 1
    • 6
  1. 1.Spoken Language Systems LaboratoryINESC-ID LisboaLisboaPortugal
  2. 2.FLUL/CLUL, Universidade de LisboaLisboaPortugal
  3. 3.ISCTE-IUL – Instituto Universitário de LisboaLisboaPortugal
  4. 4.Unbabel Inc.LisboaPortugal
  5. 5.Intelligent Agents and Synthetic Characters Group, INESC-ID LisboaLisboaPortugal
  6. 6.Instituto Superior Técnico, Universidade de LisboaLisboaPortugal

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