Phillip Kirlin

Phillip B. Kirlin and Jason Yust.
Analysis of Analysis: Using Machine Learning to Evaluate the Importance of Music Parameters for Schenkerian Analysis.
Journal of Mathematics and Music 10 (2): 127-148, 2016.
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Jason Yust and Phillip B. Kirlin
The Multileveled Rhythmic Structure of Ragtime.
In Proceedings of the 9th International Conference on Culture and Computing, pages 337-354, 2021.
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Phillip B. Kirlin
A Corpus-Based Analysis of Syncopated Patterns in Ragtime.
In Proceedings of the 21st International International Society for Music Information Retrieval Conference, pages 647-653, 2020.
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Joel Michelson, Hong Xu, and Phillip B. Kirlin
Probabilistic Generation of Ragtime Music from Classical Melodies.
In Proceedings of the Sixth International Conference on Mathematics and Computation in Music, pages 350-360, 2017. (Also appears in Springer's Lecture Notes in Computer Science)
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Phillip B. Kirlin
Global Properties of Expert and Algorithmic Hierarchical Music Analyses.
In Proceedings of the 17th International Society for Music Information Retrieval Conference, pages 640-646, 2016.
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Phillip B. Kirlin and David L. Thomas.
Extending a Model of Monophonic Hierarchical Music Analysis to Homophony.
In Proceedings of the 16th International Society for Music Information Retrieval Conference, pages 715-721, 2015.
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Phillip B. Kirlin and David D. Jensen.
Using Supervised Learning to Uncover Deep Musical Structure.
In Proceedings of the 29th AAAI Conference on Artificial Intelligence, pages 1770-1776, 2015.
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Phillip B. Kirlin.
A Data Set for Computational Studies of Schenkerian Analysis.
In Proceedings of the 15th International Society for Music Information Retrieval Conference, pages 213-218, 2014.
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Phillip B. Kirlin and David D. Jensen.
Probabilistic Modeling of Hierarchical Music Analysis.
In Proceedings of the 12th International Society for Music Information Retrieval Conference, pages 393-398, 2011.
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Phillip B. Kirlin.
Using Harmonic and Melodic Analyses to Automate the Initial Stages of Schenkerian Analysis.
In Proceedings of the 10th International Society for Music Information Retrieval Conference, pages 423-428, 2009.
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Phillip B. Kirlin and Paul E. Utgoff.
A Framework for Automated Schenkerian Analysis.
In Proceedings of the Ninth International Conference on Music Information Retrieval, pages 363-368, 2008.
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Paul E. Utgoff and Phillip B. Kirlin.
Detecting Motives and Recurring Patterns in Polyphonic Music.
In Proceedings of the International Computer Music Conference, pages 487-494, 2006.
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Phillip B. Kirlin and Paul E. Utgoff.
VoiSe: Learning To Segregate Voices In Explicit And Implicit Polyphony.
In Proceedings of the Sixth International Conference on Music Information Retrieval, pages 552-557, 2005.
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Phillip B. Kirlin.
A Probabilistic Model of Hierarchical Music Analysis.
PhD thesis, University of Massachusetts Amherst, February 2014.
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