Thesis Details
Systém pro doporučování skladeb
Bachelor's Thesis
Student: Páleník Radoslav
Academic Year: 2021/2022
Supervisor: Zbořil František, doc. Ing., Ph.D.
Language
Slovak
Abstract
This bachelor thesis aims to study and design computer program, which will be able to recognise 10 essential music genres using deep learning. This classification was implemented by convolutional neural network based on Tensorflow framework. This network process audio file into segments in form of spectograms and returns percentual propability of record being classified into specific genre by features found in spectogram.
Keywords
Convolutional neural networks, music genre, spectogram, segmentation, GTZAN, TensorFlow, image processing
Department
Degree Programme
Information Technology
Files
Status
defended, grade D
Date
15 June 2022
Reviewer
Committee
Zbořil František, doc. Ing., Ph.D. (DITS FIT BUT), předseda
Bařina David, Ing., Ph.D. (DCGM FIT BUT), člen
Hynek Jiří, Ing., Ph.D. (DIFS FIT BUT), člen
Kekely Lukáš, Ing., Ph.D. (DCSY FIT BUT), člen
Rogalewicz Adam, doc. Mgr., Ph.D. (DITS FIT BUT), člen
Bařina David, Ing., Ph.D. (DCGM FIT BUT), člen
Hynek Jiří, Ing., Ph.D. (DIFS FIT BUT), člen
Kekely Lukáš, Ing., Ph.D. (DCSY FIT BUT), člen
Rogalewicz Adam, doc. Mgr., Ph.D. (DITS FIT BUT), člen
Citation
PÁLENÍK, Radoslav. Systém pro doporučování skladeb. Brno, 2022. Bachelor's Thesis. Brno University of Technology, Faculty of Information Technology. 2022-06-15. Supervised by Zbořil František. Available from: https://www.fit.vut.cz/study/thesis/24713/
BibTeX
@bachelorsthesis{FITBT24713, author = "Radoslav P\'{a}len\'{i}k", type = "Bachelor's thesis", title = "Syst\'{e}m pro doporu\v{c}ov\'{a}n\'{i} skladeb", school = "Brno University of Technology, Faculty of Information Technology", year = 2022, location = "Brno, CZ", language = "slovak", url = "https://www.fit.vut.cz/study/thesis/24713/" }