15th Annual Conference of the International Speech Communication Association

September 14-18, 2014

Probabilistic Acoustic Volume Analysis for Speech Affected by Depression

Nicholas Cummins (1), Vidhyasaharan Sethu (1), Julien Epps (1), Jarek Krajewski (2)

(1) University of New South Wales, Australia
(2) Universität Wuppertal, Germany

Alterations in speech motor control in depressed individuals have been found to manifest as a reduction in spectral variability. In this paper we present a novel method for measuring acoustic volume — a model-based measure that is reflective of this decrease in spectral variability — and assess the ability of features resulting from this measure for indexing a speaker's level of depression. A Monte Carlo approximation that enables the computation of this measure is also outlined in this paper. Results found using the AVEC 2013 Challenge Dataset indicate there is a statistically significant reduction in acoustic variation with increasing levels of speaker depression, and using features designed to capture this change it is possible to outperform a range of conventional spectral measures when predicting a speaker's level of depression.

Full Paper

Bibliographic reference.  Cummins, Nicholas / Sethu, Vidhyasaharan / Epps, Julien / Krajewski, Jarek (2014): "Probabilistic acoustic volume analysis for speech affected by depression", In INTERSPEECH-2014, 1238-1242.