articleMay 1, 2013Closed access

New types of deep neural network learning for speech recognition and related applications: an overview

Microsoft (United States) · University of Toronto · +2 more institutions

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Abstract

In this paper, we provide an overview of the invited and contributed papers presented at the special session at ICASSP-2013, entitled “New Types of Deep Neural Network Learning for Speech Recognition and Related Applications,” as organized by the authors. We also describe the historical context in which acoustic models based on deep neural networks have been developed. The technical overview of the papers presented in our special session is organized into five ways of improving deep learning methods: (1) better optimization; (2) better types of neural activation function and better network architectures; (3) better ways to determine the myriad hyper-parameters of deep neural networks; (4) more appropriate ways…

Citation impact

1,205
total citations
FWCI
75.11
Percentile
100%
References
67
Citations per year

Authors

3

Topics & keywords

Keywords
  • Computer science
  • Artificial neural network
  • Deep learning
  • Artificial intelligence
  • Speech recognition
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