In recent years, quantitative and technical approaches to the humanities and cultural sciences have gained importance. This also affects musicology. Besides digitized sheet music documents, audio recordings of musical performances play an increasing role for this discipline. To analyze music recordings regarding relevant characteristics, signal processing and machine learning techniques need to be used in a suitable way. The application of these techniques to large music collections (corpus analysis) shows the high potential of computational audio analysis for musicological research.
In this talk, the characteristics and complexity of audio data shall be conveyed along with basic concepts of music processing algorithms. Their applications for musicology will be demonstrated with several examples and corpora of Western classical music recordings.
Lecture Slides will appear here soon.
Video footage will be added in the future.