“You sound ill, take the day off”: Automatic recognition of speech affected by upper respiratory tract infection
Nicholas Cummins, Maximilian Schmitt, Shahin Amiriparian, Jarek Krajewski, Björn Wolfgang Schuller · 2017
A combination of passive, non-invasive and nonintrusive smart monitoring technologies is currently transforming healthcare. These technologies will soon be able to provide immediate health related feedback for a range of illnesses and conditions. Such tools would be game changing for serious public health concerns, such as seasonal cold and flu, for which early diagnosis and social isolation play a key role in reducing the spread. In this regard, this paper explores, for the first times, the automated classification of individuals with Upper Respiratory Tract Infections (URTI) using recorded speech samples. Key results presented indicate that our classifiers can achieve similar results to those seen in related health-based detection tasks indicating the promise of using computational paralinguistic analysis for the detection of URTI related illnesses.