Music recordings are rife with data waiting for extraction, organization, analysis, and visualization. How can you do this in a meaningful way that facilitates better understanding of what constitutes sounded music and its place within musical life?

I propose to offer a music information retrieval, analysis, and visualization demonstration highlighting some reliable and user friendly ways of making sense of musical math. I’ll start with an overview of feature extraction from a recording of an opera aria performance and how to visualize the extracted data to create a new text of a performance. Next, I will demonstrate a way to analyze these texts (visualizations) in a way that sheds new light on the creative process. This process builds on methodologies that British scholars developed for solo piano performance; the use of it for opera is something I have not encountered elsewhere.

For the last section of my presentation, I will demonstrate how a single performance in the corpus of a performance history links to the other performances in it and the tradition that surrounds these performances. I will end with a demonstration of one way to visualize these performances in relationship with each other and analyze the complex network their instantiations of a musical work creates.