Joshua  Neumann


Joshua Neumann is a PhD candidate in historical musicology at the University of Florida, where he is a College of Fine Arts Humanities Teaching Fellow. He served two terms as the president of the Graduate Student Council and as a student senator in the UF Faculty Senate. His dissertation, “Towards Defining Tradition: Statistical Analysis, Performance, and Puccini’s Turandot,” examines the past 50+ years of performance practice tradition in productions of Puccini’s final work at New York’s Metropolitan Opera.

  • Audio feature extraction and data visualization


    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.

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