Speech recognition using recurrent neural prediction model

@article{Uchiyama2003SpeechRU,
  title={Speech recognition using recurrent neural prediction model},
  author={Toru Uchiyama and Haruhisa Takahashi},
  journal={Systems and Computers in Japan},
  year={2003},
  volume={34},
  pages={100-107}
}
The neural prediction model (NPM) proposed by Iso and Watanabe is a successful example of a speech recognition neural network with a high recognition rate. This model uses multilayer perceptrons for pattern prediction (not for pattern recognition), and achieves a recognition rate as high as 99.8% for speaker-independent isolated words. This paper proposes a recurrent neural prediction model (RNPM), and a recurrent network architecture for this model. The proposed model very significantly… CONTINUE READING
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