  Psychomotor retardation in depression has been associated with speech timing
changes from dyadic clinical interviews. In this work, we investigate speech
timing features from free-living dyadic interactions. Apart from the
possibility of continuous monitoring to complement clinical visits, a study in
free-living conditions would also allow inferring sociability features such as
dyadic interaction frequency implicated in depression. We adapted a speaker
count estimator as a dyadic interaction detector with a specificity of 89.5%
and a sensitivity of 86.1% in the DIHARD dataset. Using the detector, we
obtained speech timing features from the detected dyadic interactions in
multi-day audio recordings of 32 participants comprised of 13 healthy
individuals, 11 individuals with depression, and 8 individuals with psychotic
disorders. The dyadic interaction frequency increased with depression severity
in participants with no or mild depression, indicating a potential diagnostic
marker of depression onset. However, the dyadic interaction frequency decreased
with increasing depression severity for participants with moderate or severe
depression. In terms of speech timing features, the response time had a
significant positive correlation with depression severity. Our work shows the
potential of dyadic interaction analysis from audio recordings of free-living
to obtain markers of depression severity.
