Neural network based acoustic models for speech recognition by grouping context-dependent targets
Abstract:
Methods and systems for training a neural network include identifying weights in a neural network between a final hidden neuron layer and an output neuron layer that correspond to state matches between a neuron of the final hidden neuron layer and a respective neuron of the output neuron layer. The identified weights are initialized to a predetermined non-zero value and initializing other weights between the final hidden neuron layer and the output neuron layer to zero. The neural network is trained based on a training corpus after initialization.
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