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In the deep neural network (DNN), the hidden layers can be considered as increasingly complex feature transformations and the final softmax layer as a log-linear classifier making use of the most abstract features computed in the hidden layers. While the loglinear classifier should be different for different languages, the feature transformations can be shared across languages. In this paper we propose...
Context-dependent deep neural network hidden Markov model (CD-DNN-HMM) is a recently proposed acoustic model that significantly outperformed Gaussian mixture model (GMM)-HMM systems in many large vocabulary speech recognition (LVSR) tasks. In this paper we present our strategy of using mixed-bandwidth training data to improve wideband speech recognition accuracy in the CD-DNN-HMM framework. We show...
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