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<dc:title xml:lang="pl"><![CDATA[Acoustic analysis assessment in speech pathology detection]]></dc:title>
<dc:creator><![CDATA[Panek, Daria]]></dc:creator>
<dc:creator><![CDATA[Skalski, Andrzej]]></dc:creator>
<dc:creator><![CDATA[Gajda, Janusz (1933- )]]></dc:creator>
<dc:creator><![CDATA[Tadeusiewicz, Ryszard (1947- )]]></dc:creator>
<dc:subject xml:lang="pl"><![CDATA[linear PCA]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[non-linear PCA]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[auto-associative neural network]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[validation]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[voice pathology detection]]></dc:subject>
<dc:description xml:lang="pl"><![CDATA[Automatic detection of voice pathologies enables non-invasive, low cost and objective assessments of the presence of disorders, as well as accelerating and improving the process of diagnosis and clinical treatment given to patients.]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[In this work, a vector made up of 28 acoustic parameters is evaluated using principal component analysis (PCA), kernel principal component analysis (kPCA) and an auto-associative neural network (NLPCA) in four kinds of pathology detection (hyperfunctional dysphonia, functional dysphonia, laryngitis, vocal cord paralysis) using the a, i and u vowels, spoken at a high, low and normal pitch.]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[The results indicate that the kPCA and NLPCA methods can be considered a step towards pathology detection of the vocal folds. The results show that such an approach provides acceptable results for this purpose, with the best efficiency levels of around 100%. The study brings the most commonly used approaches to speech signal processing together and leads to a comparison of the machine learning methods determining the health status of the patient.]]></dc:description>
<dc:publisher><![CDATA[Zielona Góra: Uniwersytet Zielonogórski]]></dc:publisher>
<dc:contributor><![CDATA[Byrski, Aleksander - ed.]]></dc:contributor>
<dc:contributor><![CDATA[Kisiel-Dorohinicki, Marek - ed.]]></dc:contributor>
<dc:contributor><![CDATA[Dobrowolski, Grzegorz - ed.]]></dc:contributor>
<dc:date><![CDATA[2015]]></dc:date>
<dc:type xml:lang="pl"><![CDATA[artykuł]]></dc:type>
<dc:identifier><![CDATA[http://www.zbc.uz.zgora.pl/repozytorium/Content/79076/AMCS_2015_25_3_14.pdf]]></dc:identifier>
<dc:identifier><![CDATA[https://zbc.uz.zgora.pl/repozytorium/dlibra/publication/88907/edition/79076/content]]></dc:identifier>
<dc:identifier><![CDATA[oai:zbc.uz.zgora.pl:79076]]></dc:identifier>
<dc:source xml:lang="pl"><![CDATA[AMCS, volume 25, number 3 (2015)]]></dc:source>
<dc:source xml:lang="pl"><![CDATA[https://www.amcs.uz.zgora.pl/?action=papers&issue=62]]></dc:source>
<dc:language><![CDATA[eng]]></dc:language>
<dc:relation><![CDATA[oai:zbc.uz.zgora.pl:publication:88907]]></dc:relation>
<dc:rights xml:lang="pl"><![CDATA[Biblioteka Uniwersytetu Zielonogórskiego]]></dc:rights>
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