A New GAN-based End-to-End TTS Training Algorithm

9 Apr 2019 Haohan Guo Frank K. Soong Lei He Lei Xie

End-to-end, autoregressive model-based TTS has shown significant performance improvements over the conventional one. However, the autoregressive module training is affected by the exposure bias, or the mismatch between the different distributions of real and predicted data... (read more)

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Methods used in the Paper


METHOD TYPE
Griffin-Lim Algorithm
Phase Reconstruction
Sigmoid Activation
Activation Functions
Highway Layer
Miscellaneous Components
Residual Connection
Skip Connections
Batch Normalization
Normalization
Max Pooling
Pooling Operations
Residual GRU
Recurrent Neural Networks
BiGRU
Bidirectional Recurrent Neural Networks
Highway Network
Feedforward Networks
CBHG
Speech Synthesis Blocks
ReLU
Activation Functions
Dropout
Regularization
Dense Connections
Feedforward Networks
Tanh Activation
Activation Functions
Additive Attention
Attention Mechanisms
GRU
Recurrent Neural Networks
Tacotron
Text-to-Speech Models
Convolution
Convolutions
GAN
Generative Models