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Activity Number: 88 - Data Visualization in Practice
Type: Contributed
Date/Time: Monday, August 9, 2021 : 10:00 AM to 11:50 AM
Sponsor: Section on Statistical Graphics
Abstract #318394
Title: Similarity, Distance, and Self-Similarity in Renaissance Music
Author(s): Laura Tupper*
Companies: Williams College
Keywords: time series; similarity measures; data visualization; classification; music; digital humanities
Abstract:

The CRIM project provides a collection of Renaissance Imitation Masses: musical compositions created in deliberate dialogue with previously existing pieces. For example, a single existing chanson or madrigal could be transformed into a five-part musical setting of the Catholic Mass through a mix of quotation, expansion, and adaptation; in some cases, the same source was used by different composers to create multiple Imitation Masses. We use time series and high-dimensional data techniques to analyze these compositions' structural and stylistic characteristics. In particular, we examine measures and visualizations that reflect internal homogeneity of musical sequences, as well as shared musical behaviors across different compositions. These can be used both to characterize individual pieces and to reveal commonalities, connections, or dissimilarities between different pieces.


Authors who are presenting talks have a * after their name.

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