Fast speaker adaptation of hybrid NN/HMM model for speech recognition based on discriminative learning of speaker code

@article{AbdelHamid2013FastSA,
  title={Fast speaker adaptation of hybrid NN/HMM model for speech recognition based on discriminative learning of speaker code},
  author={Ossama Abdel-Hamid and Hui Jiang},
  journal={2013 IEEE International Conference on Acoustics, Speech and Signal Processing},
  year={2013},
  pages={7942-7946}
}
In this paper, we propose a new fast speaker adaptation method for the hybrid NN-HMM speech recognition model. The adaptation method depends on a joint learning of a large generic adaptation neural network for all speakers as well as multiple small speaker codes (one per speaker). The joint training method uses all training data along with speaker labels to update adaptation NN weights and speaker codes based on the standard back-propagation algorithm. In this way, the learned adaptation NN is… CONTINUE READING
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  • Experimental results on TIMIT have shown that it can achieve over 10% relative reduction in phone error rate by using only seven utterances for adaptation.

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