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
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
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/"
}
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