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"You sound ill, take the day off": Automatic recognition of speech affected by upper respiratory tract infection.
Annu Int Conf IEEE Eng Med Biol Soc ; 2017: 3806-3809, 2017 Jul.
Article in En | MEDLINE | ID: mdl-29060727
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.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Speech Type of study: Screening_studies Limits: Humans Language: En Journal: Annu Int Conf IEEE Eng Med Biol Soc Year: 2017 Document type: Article Country of publication:

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Speech Type of study: Screening_studies Limits: Humans Language: En Journal: Annu Int Conf IEEE Eng Med Biol Soc Year: 2017 Document type: Article Country of publication: