Chapter 8. Applications of LSTM – Generating Text

Now that we have a good understanding of the underlying mechanisms of LSTMs, such as how they solve the problem of the vanishing gradient and update rules, we can look at how to use them in NLP tasks. LSTMs are heavily employed for tasks such as text generation and image caption generation. For example, language modeling is very useful for text summarization tasks or generating captivating textual advertisements for products, where image caption generation or image annotation is very useful for image retrieval, and where a user might need to retrieve images representing some concept (for example, a cat).

The application that we will cover in this chapter is the use of an LSTM to generate new text. For this task, we will download translations of some folk stories by the Brothers Grimm. We will use these stories to train an LSTM and ask it at the end to output a fresh new story. We will process the text by breaking it into...