Densely Connected Networks for Conversational Speech Recognition

@inproceedings{Han2018DenselyCN,
  title={Densely Connected Networks for Conversational Speech Recognition},
  author={Kyu J. Han and Akshay Chandrashekaran and Jungsuk Kim and Ian R. Lane},
  booktitle={INTERSPEECH},
  year={2018}
}
In this paper we show how we have achieved the state-of-theart performance on the industry-standard NIST 2000 Hub5 English evaluation set. We propose densely connected LSTMs (namely, dense LSTMs), inspired by the densely connected convolutional neural networks recently introduced for image classification tasks. It is shown that the proposed dense LSTMs would provide more reliable performance as compared to the conventional, residual LSTMs as more LSTM layers are stacked in neural networks. With… 

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