  The cover is the face of a book and is a point of attraction for the readers.
Designing book covers is an essential task in the publishing industry. One of
the main challenges in creating a book cover is representing the theme of the
book's content in a single image. In this research, we explore ways to produce
a book cover using artificial intelligence based on the fact that there exists
a relationship between the summary of the book and its cover. Our key
motivation is the application of text-to-image synthesis methods to generate
images from given text or captions. We explore several existing text-to-image
conversion techniques for this purpose and propose an approach to exploit these
frameworks for producing book covers from provided summaries. We construct a
dataset of English books that contains a large number of samples of summaries
of existing books and their cover images. In this paper, we describe our
approach to collecting, organizing, and pre-processing the dataset to use it
for training models. We apply different text-to-image synthesis techniques to
generate book covers from the summary and exhibit the results in this paper.
