K-means clustering of historical Beethoven sonata recordings identifies multiple stable tempo traditions per movement that persist independently over eight decades instead of showing uniform change.
An Interdisciplinary Review of Music Performance Analy- sis
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
fields
cs.SD 4years
2026 4verdicts
UNVERDICTED 4representative citing papers
A cumulative timestamp protocol yields millisecond-resolution bar-level BPM data for polyphonic chamber music and captures expressive timing missed by automated detectors, demonstrated on over 100 Beethoven sonata recordings.
Cosmodoit is a modular Python package that pipelines performance-to-score alignment with symbolic and audio feature extraction to enable efficient, dependency-aware processing of performed music.
The paper introduces and demonstrates a complementary set of five visualizations including tempographs, spline-smoothed histograms, ridgeline plots, stacked bar charts, and combination charts for bar-level tempo data from Beethoven piano and cello sonata recordings spanning 1930-2012.
citing papers explorer
-
Coexisting Tempo Traditions in Beethoven's Piano and Cello Sonatas: A K-means Clustering Analysis of Recorded Performances, 1930-2012
K-means clustering of historical Beethoven sonata recordings identifies multiple stable tempo traditions per movement that persist independently over eight decades instead of showing uniform change.
-
A Manual Bar-by-Bar Tempo Measurement Protocol for Polyphonic Chamber Music Recordings: Design, Validation, and Application to Beethoven's Piano and Cello Sonatas
A cumulative timestamp protocol yields millisecond-resolution bar-level BPM data for polyphonic chamber music and captures expressive timing missed by automated detectors, demonstrated on over 100 Beethoven sonata recordings.
-
Cosmodoit: A Python Package for Adaptive, Efficient Pipelining of Feature Extraction from Performed Music
Cosmodoit is a modular Python package that pipelines performance-to-score alignment with symbolic and audio feature extraction to enable efficient, dependency-aware processing of performed music.
-
A Complementary Visualisation Suite for Empirical Performance Analysis: Tempographs, Histograms, Ridgeline Plots, Stacked Bar Charts, and Combination Charts Applied to Beethoven's Piano and Cello Sonatas
The paper introduces and demonstrates a complementary set of five visualizations including tempographs, spline-smoothed histograms, ridgeline plots, stacked bar charts, and combination charts for bar-level tempo data from Beethoven piano and cello sonata recordings spanning 1930-2012.