The architecture of the model is shown in Figure 5. Figure 5. Model architecture diagram of the deep convolutional autoencoder. The input to the model is a 9 × 24 matrix, where 9 represents the 9 ...

This paper proposes a complex recurrent variational autoencoder (VAE) framework, for modeling time series data, particularly speech signals. First, to account for the temporal structure of speech ...

We address this problem using the latent space of the β -Variational Autoencoder ( β -VAE). We use the fact that compact latent space generated by an appropriately selected β - VAE will encode the ...