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Beat tracking systems for music recordings
Staňková, Karolína ; Miklánek, Štěpán (referee) ; Ištvánek, Matěj (advisor)
This master thesis deals with systems for detecting rhythmic structures of music recordings. The field of Music Information Retrieval (MIR) allows us to examine the harmonic and tonal properties of music, rhythm, tempo, etc., and has uses in academic and commercial sphere. Various algorithms are used in the detection of rhythmic structures. However, today, most new methods use neural networks. This work aims to summarize the current research results of systems for detecting beats and tempo, to describe methods of calculating and evaluating the parameters of music recordings, and to implement a program that allows comparison of available detection systems. The result of the work is a script in the Python language, which uses six different systems to detect the rhythmic structure of test recordings. It then checks the outputs of the algorithms according to the given reference and compares the given systems with each other using several evaluation values. It uses two datasets as a reference—one of them is publicly available and the other was created by the author of this thesis (including annotations, i.e., reference beat times, for the sample recordings). The program allows user to see the results in graphs and play any of the sample recordings with detected beat times.
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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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Beat tracking systems for music recordings
Staňková, Karolína ; Miklánek, Štěpán (referee) ; Ištvánek, Matěj (advisor)
This master thesis deals with systems for detecting rhythmic structures of music recordings. The field of Music Information Retrieval (MIR) allows us to examine the harmonic and tonal properties of music, rhythm, tempo, etc., and has uses in academic and commercial sphere. Various algorithms are used in the detection of rhythmic structures. However, today, most new methods use neural networks. This work aims to summarize the current research results of systems for detecting beats and tempo, to describe methods of calculating and evaluating the parameters of music recordings, and to implement a program that allows comparison of available detection systems. The result of the work is a script in the Python language, which uses six different systems to detect the rhythmic structure of test recordings. It then checks the outputs of the algorithms according to the given reference and compares the given systems with each other using several evaluation values. It uses two datasets as a reference—one of them is publicly available and the other was created by the author of this thesis (including annotations, i.e., reference beat times, for the sample recordings). The program allows user to see the results in graphs and play any of the sample recordings with detected beat times.
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