Natural language processing is one of the most powerful concepts in modern linguistics and computer science, bridging the understanding of language from human to machine, and in turn programming machines so they can perform complex linguistic tasks on their own. This short video introduces learners to the key concepts of word embeddings and how they can be used in digital humanities projects.
The foundational skills in Distant Viewing and computer vision are increasingly relevant in the Digital Humanities, yet educational resources are often aimed at those with a background in computer science and statistics. For example, machine learning and digital image processing are fundamental to the Computational Humanities, but many scholars in the Digital Humanities lack accessible training in these areas.
The goal of this project was to create a focused course enabling students to acquire essential skills in computer vision, specifically tailored for Digital Humanists. Upon completing this course, students will possess a foundational understanding of digital image representation, computer vision methodologies, and machine learning techniques, all contextualized within a Digital Humanities framework.
This class is part of the project "Computer Vision for Digital Humanists" and licensed Creative Commons BY NC SA. This project (2023) was funded by CLARIAH-AT with the support of BMBWF. It was made possible by major contributions from the ERC DiDip project (From Digital to Distant Diplomatics). The video was produced by Moving Stills.
The goal of the project "Computer Vision for Digital Humanists" was the creation of educational self-learning resources on Computer Vision specifically for Digital Humanities, consisting of slide decks, Jupyter Notebooks with practical exercises in Python as well as teaching videos ( see the YouTube playlist. They cover a range of topics from the basics of computer vision and machine learning to training custom deep learning models for one's own historical data.
In this lecture from the Austrian Centre for Digital Humanities and Cultural Heritage (ADCH-CH), Dirk Hovy gives an introduction to the method called embeddings, and showcases several applications of it. Hovy shows how they capture regional variation at an intra- and interlingual level, how they distinguish varieties and linguistic resources, and how they allow for the assessment of changing societal norms and associations.
