However, we found the ADEM model learned more effectively when this embedding size was reduced.
after training VHRED, we use principal component analysis (PCA) (Pearson, 1901) to reduce the dimensionality of the context, model response, and reference response embeddings to n. We found experimentally that n = 50 provided the best performance.