INTERSPEECH 2013
14thAnnual Conference of the International Speech Communication Association

Lyon, France
August 25-29, 2013

Investigating Voice Quality as a Speaker-Independent Indicator of Depression and PTSD

Stefan Scherer, Giota Stratou, Jonathan Gratch, Louis-Philippe Morency

University of Southern California, USA

We seek to investigate voice quality characteristics, in particular on a breathy to tense dimension, as an indicator for psychological distress, i.e. depression and post-traumatic stress disorder (PTSD), within semi-structured virtual human interviews. Our evaluation identifies significant differences between the voice quality of psychologically distressed participants and not-distressed participants within this limited corpus. We investigate the capability of automatic algorithms to classify psychologically distressed speech in speaker-independent experiments. Additionally, we examine the impact of the posed questions' affective polarity, as motivated by findings in the literature on positive stimulus attenuation and negative stimulus potentiation in emotional reactivity of psychologically distressed participants. The experiments yield promising results using standard machine learning algorithms and solely four distinct features capturing the tenseness of the speaker's voice.

Full Paper

Bibliographic reference.  Scherer, Stefan / Stratou, Giota / Gratch, Jonathan / Morency, Louis-Philippe (2013): "Investigating voice quality as a speaker-independent indicator of depression and PTSD", In INTERSPEECH-2013, 847-851.