AI classification of respiratory illness through vocal biomarkers and a bespoke articulatory speech protocol

Speech biomarkers represent a powerful indicator for detecting, monitoring and categorising neurological, psychological , pathological and pulmonary conditions. Facilitated by advances in computational power and artificial intelligence (AI) techniques, we present a novel ecosystem for data acquisition , analysis and storage, using an articulatory speech task. By automatically segmenting, aligning and extracting features from the vocal recordings, we present a feature extraction pipeline toward the classification of pathological conditions, specifically respiratory disease through recorded voice. Data is stored within a Trusted Research Environment, for which this work also presents a range of ethical considerations