Computational Harmonic Analysis and Prediction in the Bach Chorales
dc.contributor.author | Zabriskie, Hugh Paul | |
dc.date.accessioned | 2019-03-26T10:41:19Z | |
dc.date.created | 2016-05 | |
dc.date.issued | 2016-06-21 | |
dc.date.submitted | 2016 | |
dc.identifier.uri | http://nrs.harvard.edu/urn-3:HUL.InstRepos:38811426 | * |
dc.description.abstract | During his lifetime, the Baroque composer J.S. Bach harmonized more than 300 chorale melodies, which collectively have become a pivotal body of music in Western music history and exemplify the composer’s groundbreaking compositional techniques. Bach’s harmonizations rest upon a series of compositional conventions that musicians today continue to emulate when learning to write in four-part counterpoint. By transforming the chorales into a statistical dataset, this thesis explores the ability of machine learning models to harmonically analyze chorale melodies and generate new harmonizations that exhibit the same compositional conventions Bach pioneered centuries ago. | |
dc.format.mimetype | application/pdf | |
dc.language.iso | en | |
dash.license | LAA | |
dc.subject | Computer Science | |
dc.subject | Music | |
dc.title | Computational Harmonic Analysis and Prediction in the Bach Chorales | |
dc.type | Thesis or Dissertation | |
dash.depositing.author | Zabriskie, Hugh Paul | |
dc.date.available | 2019-03-26T10:41:19Z | |
thesis.degree.date | 2016 | |
thesis.degree.grantor | Harvard College | |
thesis.degree.level | Undergraduate | |
thesis.degree.name | AB | |
dc.type.material | text | |
thesis.degree.department | Computer Science | |
dash.identifier.vireo | http://etds.lib.harvard.edu/college/admin/view/121 | |
dash.author.email | hugh.zabriskie@gmail.com |
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FAS Theses and Dissertations [6136]