Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition
@article{Dahl2012ContextDependentPD, title={Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition}, author={G. Dahl and Dong Yu and L. Deng and A. Acero}, journal={IEEE Transactions on Audio, Speech, and Language Processing}, year={2012}, volume={20}, pages={30-42} }
We propose a novel context-dependent (CD) model for large-vocabulary speech recognition (LVSR) that leverages recent advances in using deep belief networks for phone recognition. We describe a pre-trained deep neural network hidden Markov model (DNN-HMM) hybrid architecture that trains the DNN to produce a distribution over senones (tied triphone states) as its output. The deep belief network pre-training algorithm is a robust and often helpful way to initialize deep neural networks… CONTINUE READING
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