Information-Theoretic Measures Predict the Human Judgment of Rhythm Complexity
- Submitting institution
-
Goldsmiths' College
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1977
- Type
- D - Journal article
- DOI
-
10.1111/cogs.12347
- Title of journal
- Cognitive Science
- Article number
- -
- First page
- 800
- Volume
- 41
- Issue
- 3
- ISSN
- 0364-0213
- Open access status
- Out of scope for open access requirements
- Month of publication
- April
- Year of publication
- 2016
- URL
-
http://research.gold.ac.uk/id/eprint/22426/
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
3
- Research group(s)
-
-
- Citation count
- 5
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper establishes that, amongst five measures of algorithmic and information theoretic complexity, only entropy rate correlates strongly with rhythm comprehension. The finding is significant because, although Kolmogorov complexity has been linked to subjective perception of rhythm complexity, departure from periodicity, as measured by entropy rate, correlates with objective rhythm comprehension. The result aligns with growing evidence that formal complexity measures capture aspects of music but additionally introduces entropy rate to music psychological study and proves a connection between entropy rate and objectively measured rhythm complexity.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -