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Enhanced Living by Assessing Voice Pathology Using a Co-Occurrence Matrix
Department of Computer Engineering, College of Computer and Information Sciences, King Saud University, Riyadh .
Department of Software Engineering, College of Computer and Information Sciences, King Saud University, Riyadh .
Department of Software Engineering, College of Computer and Information Sciences, King Saud University, Riyadh .
Department of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh .
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Number of Authors: 5
2017 (English)In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 17, no 2, 267Article in journal (Refereed) Published
Abstract [en]

large number of the population around the world suffers from various disabilities. Disabilities affect not only children but also adults of different professions. Smart technology can assist the disabled population and lead to a comfortable life in an enhanced living environment (ELE). In this paper, we propose an effective voice pathology assessment system that works in a smart home framework. The proposed system takes input from various sensors, and processes the acquired voice signals and electroglottography (EGG) signals. Co-occurrence matrices in different directions and neighborhoods from the spectrograms of these signals were obtained. Several features such as energy, entropy, contrast, and homogeneity from these matrices were calculated and fed into a Gaussian mixture model-based classifier. Experiments were performed with a publicly available database, namely, the Saarbrucken voice database. The results demonstrate the feasibility of the proposed system in light of its high accuracy and speed. The proposed system can be extended to assess other disabilities in an ELE.

Place, publisher, year, edition, pages
2017. Vol. 17, no 2, 267
National Category
Media and Communication Technology
Research subject
Mobile and Pervasive Computing
Identifiers
URN: urn:nbn:se:ltu:diva-61833DOI: 10.3390/s17020267PubMedID: 28146069ScopusID: 2-s2.0-85011031796OAI: oai:DiVA.org:ltu-61833DiVA: diva2:1071642
Note

Validerad; 2017; Nivå 2; 2017-02-06 (andbra)

Available from: 2017-02-06 Created: 2017-02-06 Last updated: 2017-03-14Bibliographically approved

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CiteExportLink to record
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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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More styles
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  • de-DE
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  • fi-FI
  • nn-NO
  • nn-NB
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  • Other locale
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Output format
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