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Fusing voice and query data for non-invasive detection of laryngeal disorders
Kaunas University of Technology, Kaunas, Lithuania.
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.ORCID iD: 0000-0003-2185-8973
Kaunas University of Technology, Kaunas, Lithuania.
Kaunas University of Technology, Kaunas, Lithuania.
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2015 (English)In: Expert systems with applications, ISSN 0957-4174, E-ISSN 1873-6793, Vol. 42, no 22, 8445-8453 p.Article in journal (Refereed) Published
Abstract [en]

Topic of this study is exploration and fusion o fnon-invasive measurements for an accurate detection of pathological larynx. Measurements for human subject encompass answers to items of a specific survey and information extracted by the openSMILE toolkit from several audio recordings of sustained phonation (vowel/a/).

Place, publisher, year, edition, pages
Kidlington: Pergamon Press, 2015. Vol. 42, no 22, 8445-8453 p.
Keyword [en]
Ensemble methods, Random forest, Variable importance, Imputation, Affinity analysis, Voice pathology detection
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:hh:diva-29487DOI: 10.1016/j.eswa.2015.07.001ISI: 000361923100007Scopus ID: 2-s2.0-84940461705OAI: oai:DiVA.org:hh-29487DiVA: diva2:855194
Note

Initial results, excluding experiments with imputation and variable importance, were presented in the 14th International Conference on Artificial Intelligence, Knowledge Engineering and Data Bases (Vaiciukynas et al., 2015). This research was funded by a grant (No. MIP-075/2015) from the Research Council of Lithuania.

Available from: 2015-09-19 Created: 2015-09-19 Last updated: 2016-11-24Bibliographically approved

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Verikas, AntanasHållander, Magnus
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CiteExportLink to record
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Citation style
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Language
  • de-DE
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Output format
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