Efficient Training and Evaluation of Recurrent Neural Network Language Models for Automatic Speech Recognition

@article{Chen2016EfficientTA,
  title={Efficient Training and Evaluation of Recurrent Neural Network Language Models for Automatic Speech Recognition},
  author={Xie Chen and Xunying Liu and Yongqiang Wang and Mark J. F. Gales and Philip C. Woodland},
  journal={IEEE/ACM Transactions on Audio, Speech, and Language Processing},
  year={2016},
  volume={24},
  pages={2146-2157}
}
Recurrent neural network language models RNNLMs are becoming increasingly popular for a range of applications including automatic speech recognition. An important issue that limits their possible application areas is the computational cost incurred in training and evaluation. This paper describes a series of new efficiency improving approaches that allows RNNLMs to be more efficiently trained on graphics processing units GPUs and evaluated on CPUs. First, a modified RNNLM architecture with a… CONTINUE READING
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