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Variational Cross domain Natural Language Generation for Spoken Dialogue Systems

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Figure

Figure 1: Semantically Conditioned VariationalAutoencoder with a semantic representation (SR)main, the dialogue act (DA) and the slots ofas the condition
Figure 2: 2D-projection of z for each data point inthe test set, with two different colouring-schemes.
Figure 3:Comparison between SCVAE andSCLSTM with limited training data.

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