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  <title>DSpace Collection:</title>
  <link rel="alternate" href="http://localhost:8080/xmlui/handle/123456789/2301" />
  <subtitle />
  <id>http://localhost:8080/xmlui/handle/123456789/2301</id>
  <updated>2026-06-23T06:32:22Z</updated>
  <dc:date>2026-06-23T06:32:22Z</dc:date>
  <entry>
    <title>Feature Selection of Abnormal Speech using Binary Tree</title>
    <link rel="alternate" href="http://localhost:8080/xmlui/handle/123456789/2302" />
    <author>
      <name>Laghate, Snehal S</name>
    </author>
    <author>
      <name>Bhabad2, Prof.Sanjivani S</name>
    </author>
    <id>http://localhost:8080/xmlui/handle/123456789/2302</id>
    <updated>2019-08-14T08:59:24Z</updated>
    <published>2016-08-03T00:00:00Z</published>
    <summary type="text">Title: Feature Selection of Abnormal Speech using Binary Tree
Authors: Laghate, Snehal S; Bhabad2, Prof.Sanjivani S
Abstract: Speech problems are faced by Articulatory handicapped people. To understand the problems it is&#xD;
necessary to create database and develop new and improved feature selection technique for reliable, robust and accurate&#xD;
recognition of spoken word. This paper describes novel method of automatic feature selection for abnormal speech&#xD;
which helps to improve performance and accuracy of system. The database created is eleven digits from zero to ten for&#xD;
ten persons each being recorded ten times. Twelve features considered with 183 parameter gives 4096 binary&#xD;
combination of features for eleven digits. The results obtained using MATLAB 12B gives 70% accuracy for digit two&#xD;
for sixteen combinations of feature</summary>
    <dc:date>2016-08-03T00:00:00Z</dc:date>
  </entry>
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