Skip Connection Blocks
ParaNet Convolution Block
Introduced by Peng et al. in Non-Autoregressive Neural Text-to-SpeechA ParaNet Convolution Block is a convolutional block that appears in the encoder and decoder of the ParaNet text-to-speech architecture. It consists of a 1-D convolution with a gated linear unit (GLU) and a residual connection. It is similar to the DV3 Convolution Block.
Source: Non-Autoregressive Neural Text-to-Speech
Papers
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Usage Over Time
Components
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Convolution
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Convolutions | |
Dropout
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Regularization | |
GLU
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Activation Functions | |
Residual Connection
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Skip Connections |
