RNN research for future automatic dialog generation
The future of chatbots lies in producing dialogs automatically, based on data logging dialogs, their cognitive meanings, the personal profile of a user, and more. As RNNs progress, we will get closer to this approach. There are many generative approaches that can produce automatic sequences of sounds and texts. Understanding an RNN is a good place to start.
An RNN model is based on sequences, in this case, words. It analyzes anything in a sequence, including images. To speed the mind-dataset process up, data augmentation can be applied here, exactly as it is to images in other models.
A first look at its graph data flow structure shows that an RNN is a neural network like the others previously explored. The following diagram shows a conceptual view of an RNN:
Figure 16.15: Data flow structure
The y inputs (test data) go to the loss function (Loss_Train). The x inputs (training data) will be transformed...
