Simplifying very deep convolutional neural network architectures for robust speech recognition

@article{Rownicka2017SimplifyingVD,
  title={Simplifying very deep convolutional neural network architectures for robust speech recognition},
  author={Joanna Rownicka and Steve Renals and Peter Bell},
  journal={2017 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)},
  year={2017},
  pages={236-243}
}
Very deep convolutional neural networks (VDCNNs) have been successfully used in computer vision. More recently VDCNNs have been applied to speech recognition, using architectures adopted from computer vision. In this paper, we experimentally analyse the role of the components in VDCNN architectures for robust speech recognition. We have proposed a number of simplified VDCNN architectures, taking into account the use of fully-connected layers and down-sampling approaches. We have investigated… 
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