Robust speech recognition based on joint model and feature space optimization of hidden Markov models

@article{Moon1997RobustSR,
  title={Robust speech recognition based on joint model and feature space optimization of hidden Markov models},
  author={Seokyong Moon and Jenq-Neng Hwang},
  journal={IEEE transactions on neural networks},
  year={1997},
  volume={8 2},
  pages={194-204}
}
The hidden Markov model (HMM) inversion algorithm, based on either the gradient search or the Baum-Welch reestimation of input speech features, is proposed and applied to the robust speech recognition tasks under general types of mismatch conditions. This algorithm stems from the gradient-based inversion algorithm of an artificial neural network (ANN) by viewing an HMM as a special type of ANN. Given input speech features s, the forward training of an HMM finds the model parameters lambda… CONTINUE READING
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