Music Generation and Evaluation Using R

Honors College Thesis

Öffentlich Deposited

Citeable URL: https://ir.library.oregonstate.edu/concern/honors_college_theses/q524jv984

Descriptions

Attribute Name	Values
Creator	Lanz, Andrea L.
Abstract	The main goal of this project is to implement an algorithmic music composition procedure and present all procedures and results in a reproducible fashion by creating a web application produced by R. To approach the implementation of the algorithmic composition of music, we start by exploring various models, but ultimately we sample musical notes using a stochastic approach, specifically by employing a Hidden Markov Model using methods found in an article titled "Classical Music Composition Using State Space Models'' authored by Anna K. Yanchenko and Sayan Mukherjee. The process of music generation and evaluation will be documented and made reproducible by the development of a complementary web application to allow for easy visualization, verification, and widespread use of the developed methods.
License	All rights reserved
Resource Type	Honors College Thesis
Date Issued	2020-03-05
Degree Level	Bachelor's
Degree Name	Honors Bachelor of Science (H.B.S.)
Degree Field	Mathematics
Degree Grantor	Oregon State University
Commencement Year	2020
Advisor	Wickham, Charlotte
Committee Member	Emerson, Sarah Bokil, Vrushali
Non-Academic Affiliation	Oregon State University. Honors College
Subject	Hidden Markov models
Urheberrechts-Erklärung	In Copyright
Publisher	Oregon State University
Peer Reviewed	No
Language	English [eng]

Parents:

This work has no parents.

In Collection:

Miniaturansicht	Titel	Hochladedatum	Sichtbarkeit	Aktionen
	LanzAndreaL2020.pdf	2020-03-11	Öffentlich	Herunterladen