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  <title>DSpace Collection:</title>
  <link rel="alternate" href="http://localhost:8080/xmlui/handle/123456789/2299" />
  <subtitle />
  <id>http://localhost:8080/xmlui/handle/123456789/2299</id>
  <updated>2026-06-23T06:32:44Z</updated>
  <dc:date>2026-06-23T06:32:44Z</dc:date>
  <entry>
    <title>Effect of Pre-processing along with MFCC Parameters in Speech Recognition</title>
    <link rel="alternate" href="http://localhost:8080/xmlui/handle/123456789/2300" />
    <author>
      <name>Chavan, Ankita S.</name>
    </author>
    <author>
      <name>Munot(Bhabad, Mrs.S. S</name>
    </author>
    <id>http://localhost:8080/xmlui/handle/123456789/2300</id>
    <updated>2019-08-14T08:51:30Z</updated>
    <published>2016-06-01T00:00:00Z</published>
    <summary type="text">Title: Effect of Pre-processing along with MFCC Parameters in Speech Recognition
Authors: Chavan, Ankita S.; Munot(Bhabad, Mrs.S. S
Abstract: This paper gives brief description about feature extraction technique using MFCC. MFCC is mostly used in Automatic Speech Recognition System. Feature extraction plays an important role in ASR, which provides the set of main features. This paper includes the results for effects of normalization, down-sampling and parameter changes like window size, linear spacing. Speech recognition means pattern recognition problem, so classification is done on data using minimum distance classifier. Training and testing data are different. For down-sampling i.e Fs/4 more accuracy is achieved than normalization.</summary>
    <dc:date>2016-06-01T00:00:00Z</dc:date>
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