On Every Note a Griff: Looking for a Useful Representation of Basso Continuo Performance Style
🤖 AI Summary
This study addresses the challenge of effectively characterizing individualized styles in Baroque figured bass improvisation. Drawing on the aligned dataset ACoRD, it proposes a historically informed “griff” representation inspired by historical treatises, which groups multiple performed notes corresponding to the same notated pitch according to their onset times. This approach constructs a feature space that preserves structural relationships while remaining invariant under transposition. For the first time, it establishes a computationally tractable and historically grounded framework for stylistic analysis of basso continuo realizations. Through MIDI processing, griff extraction, and statistical modeling, two experiments demonstrate the method’s efficacy in distinguishing improvisational styles across different performers.
Application Category
📝 Abstract
Basso continuo is a baroque improvisatory accompaniment style which involves improvising multiple parts above a given bass line in a musical score on a harpsichord or organ. Basso continuo is not merely a matter of history; moreover, it is a historically inspired living practice, and The Aligned Continuo Dataset (ACoRD) records the first sample of modern-day basso continuo playing in the symbolic domain. This dataset, containing 175 MIDI recordings of 5 basso continuo scores performed by 7 players, allows us to start observing and analyzing the variety that basso continuo improvisation brings. A recently proposed basso continuo performance-to-score alignment system provides a way of mapping improvised performance notes to score notes. In order to study aligned basso continuo performances, we need an appropriate feature representation. We propose griff, a representation inspired by historical basso continuo treatises. It enables us to encode both pitch content and structure of a basso continuo realization in a transposition-invariant way. Griffs are directly extracted from aligned basso continuo performances by grouping together performance notes aligned to the same score note in a onset-time ordered way, and they provide meaningful tokens that form a feature space in which we can analyze basso continuo performance styles. We statistically describe griffs extracted from the ACoRD dataset recordings, and show in two experiments how griffs can be used for statistical analysis of individuality of different players'basso continuo performance styles. We finally present an argument why it is desirable to preserve the structure of a basso continuo improvisation in order to conduct a refined analysis of personal performance styles of individual basso continuo practitioners, and why griffs can provide a meaningful historically informed feature space worthy of a more robust empirical validation.
Problem
Research questions and friction points this paper is trying to address.
basso continuo
performance representation
improvisation
feature representation
performance style
Innovation
Methods, ideas, or system contributions that make the work stand out.
griff
basso continuo
performance representation
symbolic music analysis
improvisation style
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