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Implementation of CNN in the view of mini-batch DNN training for efficient second order optimization
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  • Journal title : Phonetics and Speech Sciences
  • Volume 8, Issue 2,  2016, pp.23-30
  • Publisher : The Korean Society of Speech Sciences
  • DOI : 10.13064/KSSS.2016.8.2.023
 Title & Authors
Implementation of CNN in the view of mini-batch DNN training for efficient second order optimization
Song, Hwa Jeon; Jung, Ho Young; Park, Jeon Gue;
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 Abstract
This paper describes some implementation schemes of CNN in view of mini-batch DNN training for efficient second order optimization. This uses same procedure updating parameters of DNN to train parameters of CNN by simply arranging an input image as a sequence of local patches, which is actually equivalent with mini-batch DNN training. Through this conversion, second order optimization providing higher performance can be simply conducted to train the parameters of CNN. In both results of image recognition on MNIST DB and syllable automatic speech recognition, our proposed scheme for CNN implementation shows better performance than one based on DNN.
 Keywords
automatic speech recognition;DNN;CNN;second order optimization;
 Language
Korean
 Cited by
 References
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