Embedding-Based Speaker Adaptive Training of Deep Neural Networks

17 Oct 2017 Xiaodong Cui Vaibhava Goel George Saon

An embedding-based speaker adaptive training (SAT) approach is proposed and investigated in this paper for deep neural network acoustic modeling. In this approach, speaker embedding vectors, which are a constant given a particular speaker, are mapped through a control network to layer-dependent element-wise affine transformations to canonicalize the internal feature representations at the output of hidden layers of a main network... (read more)

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