ISCA Archive Interspeech 2013
ISCA Archive Interspeech 2013

Investigating voice quality as a speaker-independent indicator of depression and PTSD

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

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.


doi: 10.21437/Interspeech.2013-240

Cite as: Scherer, S., Stratou, G., Gratch, J., Morency, L.-P. (2013) Investigating voice quality as a speaker-independent indicator of depression and PTSD. Proc. Interspeech 2013, 847-851, doi: 10.21437/Interspeech.2013-240

@inproceedings{scherer13_interspeech,
  author={Stefan Scherer and Giota Stratou and Jonathan Gratch and Louis-Philippe Morency},
  title={{Investigating voice quality as a speaker-independent indicator of depression and PTSD}},
  year=2013,
  booktitle={Proc. Interspeech 2013},
  pages={847--851},
  doi={10.21437/Interspeech.2013-240}
}