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Interpreting Rhythm as Parsing: Syntactic-Processing Operations Predict the Migration of Visual Flashes as Perceived
Gabriele Cecchetti1, Cédric A Tomasini1, Steffen A Herff1,2
1Digital and Cognitive Musicology Lab, École Polytechnique Fédérale de Lausanne.
Cognitive Science
|December 1, 2023
Summary
This study models music rhythm interpretation as syntactic parsing, similar to language processing. Rhythmic processing operations predict listener performance, offering a cognitive framework for musical understanding.
Area of Science:
- Cognitive Science
- Music Cognition
- Computational Linguistics
Background:
- Music interpretation involves attributing syntactic relationships to sequential events, analogous to language processing.
- Previous computational models focused on harmony; this study addresses rhythm in Western tonal music.
- A formal grammar for rhythmic interpretation and dependency locality theory inform the cognitive processing model.
Purpose of the Study:
- To propose a novel framework for modeling the cognitive processing of musical rhythm interpretation.
- To investigate the moment-by-moment execution of processing operations in rhythmic interpretation.
- To provide an empirical proof-of-concept for modeling music interpretation as syntactic parsing.
Main Methods:
- Developed a music-theoretically motivated grammar for rhythmic interpretation (preparation, syncopation, split).
- Applied principles from dependency locality theory to predict processing complexity.
- Conducted a behavioral experiment with 100 listeners reproducing visual flash locations during rhythmic excerpt playback.
Main Results:
- The hypothesized execution of syntactic-processing operations significantly predicted observed displacements in flash location reproduction.
- Results are consistent with theoretical predictions, controlling for confounding factors.
- This study presents a first empirical proof-of-concept for the proposed cognitive model.
Conclusions:
- Musical rhythm interpretation can be modeled as syntactic parsing with algorithmic similarities to linguistic processing.
- The proposed framework offers a way to model the cognitive processes underlying music interpretation.
- Further large-scale testing is warranted to validate the theoretical predictions.
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