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<record>
  <title>Speech Classification Based on FFT and ANN Algorithms</title>
  <journal>Journal of E-Technology</journal>
  <author>Shaima A. Abushaala, Salma N. Ben Hmeida, Laila Y. Fannas</author>
  <volume>5</volume>
  <issue>2</issue>
  <year>2014</year>
  <doi></doi>
  <url>http://www.dline.info/jet/fulltext/v5n2/1.pdf</url>
  <abstract>This research presents a speech classification based on feature extraction using Fast Fourier Transform (FFT) and classified by Artificial Neural Network (ANN). Each speech signal will be represented by a vector. The feature vector will constitute the input to the ANN. The collection of speech signal will be divided into two sets. One set will be used for training the ANN in a supervised fashion. The other set which is never seen by the ANN will be used for testing. After training, the ANN will be tested for classification of the speech When the speech is classified correctly.</abstract>
</record>
