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Computational Methods for Comparative Music Performance Analysis
Ištvánek, Matěj ; Róka,, Rastislav (referee) ; Jirásek, Ondřej (referee) ; Smékal, Zdeněk (advisor)
Zvyšující se dostupnost digitálního hudebního obsahu a různých interpretací hudebních děl zároveň podněcuje vývoj výpočetních metod oboru získávání hudebních informací (MIR). Tento rozvoj ale nemusí být vždy reflektován v souvisejících oblastech – například v analýze interpretačního výkonu (MPA). Hlavním tématem této disertační práce je využití výpočetních metod a digitálního zpracování hudby pro cíle MPA. Tato práce se zabývá principy MIR pro analýzu a porovnání rozdílů hudebních výkonů a jejich parametrů. Práce analyzuje limitace detektorů nástupů tónů a dob založených na konvenčních přístupech a na strojovém učení, při degradaci vstupního signálu, snížení vzorkovací frekvence, nebo v komplexnějších hudebních strukturách. Dále ukazuje možnosti použití hudební synchronizace, extrakce parametrů a výběru příznaků na originálních datech smyčcových kvartetů pro binární klasifikaci původu interpretů. Na závěr demonstruje vyvíjený software pro komparativní analýzu hudby, který kombinuje přívětivé uživatelské prostředí pro přehrávání, navigaci a vizualizaci dat hudebního výkonu s výpočetními metodami MIR.
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Game Environment from Music
Vaněk, Jiří ; Fapšo, Michal (referee) ; Hradiš, Michal (advisor)
The topic of this work is game environment generation from music. The main subject of this work is the music analysis. I am dealing with the problem of finding relevant information in music, which would be useful for game generating. The design of the system for music analysis, presented in this work, is based on the theory of signal processing and statistical classification. The proposed analysis of music is focused mainly on a beat detection, musical genre recognition and song segmentation. The second part of the work deals with the design of a game, which generates its environment from the data obtained in the music analysis. I have implemented the complete system for the music analysis and a prototype of the game, in which it is possible to evaluate the results from the analysis. The implementation and the achieved results are described in the conclusion of this work.
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Automatic Generation of Steps for DDR
Skála, František ; Glembek, Ondřej (referee) ; Černocký, Jan (advisor)
The goal of this work is to draft methods suitable for automatic creation of step-files from music files for a DDR computer dance game. This problem is divided into two main parts - beat detection, thus determining the song tempo, and determination of steps itselves. Beat detection is based on detection of energy growths in particual frequency subbands and following statistical alignment of results. Step creation works similarly, but it focuses on detection of all intense moments of music and contains a logic for placing steps into different directions. Testing by users showed that application has the potential to address players seeking set of simple steps for their favourite songs. The quality of beat detection gives field for application of these methods even beyond scope of example application. This document also suggest a few possible improvements of used methods.
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Analysis of automatic parameter extraction on piano recordings
Kaplan, Josef ; Miklánek, Štěpán (referee) ; Ištvánek, Matěj (advisor)
This bachelor thesis deals with the analysis of the accuracy of automatic extraction of parameters, mainly of piano recordings. The given issue is described both from a technical and a musical perspective. This thesis summarizes knowledge from the field of music theory and the automatic detection of parameters that can be obtained from musical piano recordings. This thesis is focused on detecting onsets, beats, downbeats, pitch estimation and tempo. The analysis of piano recordings is realized using the Python programming language. The output is scripts that perform parameter detection based on user-selected methods that are commonly used to calculate parameters. The result is also testing the accuracy of individual methods based on annotations from different datasets, focusing primarily on piano recordings. The final part contains an evaluation based on selected metrics with an objective comparison.
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Automatic Generation of Steps for DDR
Skála, František ; Glembek, Ondřej (referee) ; Černocký, Jan (advisor)
The goal of this work is to draft methods suitable for automatic creation of step-files from music files for a DDR computer dance game. This problem is divided into two main parts - beat detection, thus determining the song tempo, and determination of steps itselves. Beat detection is based on detection of energy growths in particual frequency subbands and following statistical alignment of results. Step creation works similarly, but it focuses on detection of all intense moments of music and contains a logic for placing steps into different directions. Testing by users showed that application has the potential to address players seeking set of simple steps for their favourite songs. The quality of beat detection gives field for application of these methods even beyond scope of example application. This document also suggest a few possible improvements of used methods.
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Game Environment from Music
Vaněk, Jiří ; Fapšo, Michal (referee) ; Hradiš, Michal (advisor)
The topic of this work is game environment generation from music. The main subject of this work is the music analysis. I am dealing with the problem of finding relevant information in music, which would be useful for game generating. The design of the system for music analysis, presented in this work, is based on the theory of signal processing and statistical classification. The proposed analysis of music is focused mainly on a beat detection, musical genre recognition and song segmentation. The second part of the work deals with the design of a game, which generates its environment from the data obtained in the music analysis. I have implemented the complete system for the music analysis and a prototype of the game, in which it is possible to evaluate the results from the analysis. The implementation and the achieved results are described in the conclusion of this work.
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