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Issue 1
Sep.  2015
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JING Ya-peng, ZHENG Jun, HU Wen-xin. Belongingness of Chinese dialect speech recognition based on deep neural network[J]. Journal of East China Normal University (Natural Sciences), 2014, (1): 60-67.
Citation: JING Ya-peng, ZHENG Jun, HU Wen-xin. Belongingness of Chinese dialect speech recognition based on deep neural network[J]. Journal of East China Normal University (Natural Sciences), 2014, (1): 60-67.

Belongingness of Chinese dialect speech recognition based on deep neural network

  • Received Date: 2013-03-01
  • Rev Recd Date: 2013-06-01
  • Publish Date: 2014-01-25
  • Based on the modified QuickNet software, we proposed a supervised DNN layerwise pre-training method for dialect speech recognition. The pre-training will start from a 3-layer neural network till the maximum layer, during which we will do supervised training. The initial weights of a new layer are composed of the partial trained weights of lower level network and the randomized weights closed to the output layer. Then we will do traditional back-propagation training when the initial weights of the maximum layer network are obtained. This method achieved a relatively higher recognition rate compared with normal neural network training and can be used in mobile speech recognition apps, the recognition of dialects speech and so on.
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    [5] RUMELHART D E, HINTON G E, WILLIAMS R J. Learning representations by back-propagating errors[J]. Nature, 1986, 323(6088): 533-536.

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