The Computational Humanities (CH) group at JMU Würzburg develops methods for analyzing cultural data such as images, video, and audio recordings with applications for the humanities. For this purpose, we develop and adapt machine-learning algorithms to meet the special requirements of humanities research, which demands for multimodal, objective, robust, and interpretable methods. Applying these algorithms to comprehensive corpora allows for a large-scale view on different art genres. With this, the group is embedded into the Center for Artificial Intelligence and Data Science (CAIDAS) as well as the Centre for Philology and Digitality (ZPD) and aims for establishing multilateral connections within JMU Würzburg and beyond.
A particular focus lies on the analysis of music audio recordings, contributing to research fields such as music information retrieval, audio signal processing, machine learning, and AI. This involves the creation of multimodal datasets and the development of robust and interpretable representations. Applying the analysis algorithms to large music collections (corpus analysis) indicates the high potential of computational approaches for musicological research, thus serving as an example for exploiting cultural raw data for the digital humanities.