  Background Speech-based biomarkers have potential as a means for regular,
objective assessment of symptom severity, remotely and in-clinic in combination
with advanced analytical models. However, the complex nature of speech and the
often subtle changes associated with health mean that findings are highly
dependent on methodological and cohort choices. These are often not reported
adequately in studies investigating speech-based health assessment Objective To
develop and apply an exemplar protocol to generate a pilot dataset of healthy
speech with detailed metadata for the assessment of factors in the speech
recording-analysis pipeline, including device choice, speech elicitation task
and non-pathological variability. Methods We developed our collection protocol
and choice of exemplar speech features based on a thematic literature review.
Our protocol includes the elicitation of three different speech types. With a
focus towards remote applications, we also choose to collect speech with three
different microphone types. We developed a pipeline to extract a set of 14
exemplar speech features. Results We collected speech from 28 individuals three
times in one day, repeated at the same times 8-11 weeks later, and from 25
healthy individuals three times in one week. Participant characteristics
collected included sex, age, native language status and voice use habits of the
participant. A preliminary set of 14 speech features covering timing, prosody,
voice quality, articulation and spectral moment characteristics were extracted
that provide a resource of normative values. Conclusions There are multiple
methodological factors involved in the collection, processing and analysis of
speech recordings. Consistent reporting and greater harmonisation of study
protocols are urgently required to aid the translation of speech processing
into clinical research and practice.
