  Speech is promising as an objective, convenient tool to monitor health
remotely over time using mobile devices. Numerous paralinguistic features have
been demonstrated to contain salient information related to an individual's
health. However, mobile device specification and acoustic environments vary
widely, risking the reliability of the extracted features. In an initial step
towards quantifying these effects, we report the variability of 13 exemplar
paralinguistic features commonly reported in the speech-health literature and
extracted from the speech of 42 healthy volunteers recorded consecutively in
rooms with low and high reverberation with one budget and two higher-end
smartphones and a condenser microphone. Our results show reverberation has a
clear effect on several features, in particular voice quality markers. They
point to new research directions investigating how best to record and process
in-the-wild speech for reliable longitudinal health state assessment.
