@inproceedings{ca00304a893147509af2ddaecbdda1a1,
title = "Measuring musical rhythm similarity: Edit distance versus minimum-weight many-to-many matchings",
abstract = "Musical rhythms are represented as binary symbol sequences of sounded and silent pulses of unit-duration. A measure of distance (dissimilarity) between a pair of rhythms commonly used in music information retrieval, music perception, and musicology is the edit (Levenshtein) distance, defined as the minimum number of symbol insertions, deletions, and substitutions needed to transform one rhythm into the other. A measure of distance often used in object recognition is the minimum-weight many-to-many matching distance between the object{\textquoteright}s features. These two approaches are compared empirically, in terms of how well they predict human judgments of musical rhythm similarity, using a real-world family of Middle-Eastern rhythms.",
keywords = "Edit distance, Hungarian algorithm, Many-to-many matchings, Musical rhythm, Perception, Similarity measures",
author = "Toussaint, {Godfried T.} and Oh, {Seung Man}",
note = "Funding Information: This research was supported by a research grant from the Provost Fund at New York University Abu Dhabi, and a Research Enhancement Fund grant from the NYUAD Institute, for the project titled: Cross-Disciplinary and MultiCultural Perspectives on Musical Rhythm. The research was done while the second author was a Global Academic Fellow at New York University Abu Dhabi, United Arab Emirates. Publisher Copyright: CSREA Press {\textcopyright}.; 2016 International Conference on Artificial Intelligence, ICAI 2016 - WORLDCOMP 2016 ; Conference date: 25-07-2016 Through 28-07-2016",
year = "2016",
language = "English (US)",
series = "Proceedings of the 2016 International Conference on Artificial Intelligence, ICAI 2016 - WORLDCOMP 2016",
publisher = "CSREA Press",
pages = "186--189",
editor = "Arabnia, {Hamid R.} and {de la Fuente}, David and Roger Dziegiel and Kozerenko, {Elena B.} and LaMonica, {Peter M.} and Liuzzi, {Raymond A.} and Olivas, {Jose A.} and Todd Waskiewicz and George Jandieri and Solo, {Ashu M.G.} and Tinetti, {Fernando G.}",
booktitle = "Proceedings of the 2016 International Conference on Artificial Intelligence, ICAI 2016 - WORLDCOMP 2016",
}