'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, Bjorn Schuller

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

12 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publication2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publicationSmarter Technology for a Healthier World, EMBC 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3806-3809
Number of pages4
ISBN (Electronic)9781509028092
DOIs
StatePublished - 13 Sep 2017
Externally publishedYes
Event39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017 - Jeju Island, Korea, Republic of
Duration: 11 Jul 201715 Jul 2017

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Conference

Conference39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017
Country/TerritoryKorea, Republic of
CityJeju Island
Period11/07/1715/07/17

Keywords

  • Bag-of-Audio-Words
  • Classification
  • Feature Selection
  • Paralinguistic Analysis
  • Upper Respiratory Tract Infection

Fingerprint

Dive into the research topics of ''You sound ill, take the day off': Automatic recognition of speech affected by upper respiratory tract infection'. Together they form a unique fingerprint.

Cite this