Thesis Details
Automatické generování harmonie
Goal of this master thesis is to study harmonization based on knowledge of given melody and to design a system which will meaningfully automate this activity. In the work there iscovered basics of music theory needed for this topic and previous other approaches to this problematic. There is also covered machine learning, neural networks and recurrent neuralnetworks. In the end, there is outlined design of the system, how to make it work and how to use it. Three experiments were executed with the system. Harmonization of the melodieswere unpleasant though. A possible cause might be relatively small used neural network of the system.
music, melody, harmony, harmonization, machine learning, deep learning, Neural Networks,Recurrent Neural Networks, automatic harmonization, Google Magenta
Bartík Vladimír, Ing., Ph.D. (DIFS FIT BUT), člen
Grégr Matěj, Ing., Ph.D. (DIFS FIT BUT), člen
Matoušek Petr, doc. Ing., Ph.D., M.A. (DIFS FIT BUT), člen
Meduna Alexander, prof. RNDr., CSc. (DIFS FIT BUT), člen
Veselý Vladimír, Ing., Ph.D. (DIFS FIT BUT), člen
@mastersthesis{FITMT24140,
author = "Martin Bob\v{c}\'{i}k",
type = "Master's thesis",
title = "Automatick\'{e} generov\'{a}n\'{i} harmonie",
school = "Brno University of Technology, Faculty of Information Technology",
year = 2021,
location = "Brno, CZ",
language = "czech",
url = "https://www.fit.vut.cz/study/thesis/24140/"
}