+DS IPLE: Translating between Text and Images: Creative Storytelling with Machine Learning

The ability to translate between mediums is important for both practical and creative purposes. In this IPLE we will discuss AttnGAN, a model that can produce images from input text, and Im2Text, a model that produces text descriptions from images. We will explore the architecture of both of these models, as well as looking at some interesting practical and creative applications in this space.

This session is part of the Humanities/Social Sciences +DS track, which focuses on natural language processing for the Digital Humanities and Social Sciences. Throughout the track, students are able to work hands-on with state-of-the-art transformer models for document classification, question answering, language translation, and creative language generation.

This session is part of the Duke + Data Science (+DS) program in-person learning experiences (IPLEs). To learn more, please visit https://plus.datascience.duke.edu/