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Audio signal modelling using neural networks
Pešán, Michele ; Ištvánek, Matěj (referee) ; Miklánek, Štěpán (advisor)
Neuronové sítě vycházející z architektury WaveNet a sítě využívající rekurentní vrstvy jsou v současnosti používány jak pro syntézu lidské řeči, tak pro „black box“ modelování systémů pro úpravu akustického signálu – modulační efekty, nelineární zkreslovače apod. Úkolem studenta bude shrnout dosavadní poznatky o možnostech využití neuronových sítí při modelování akustických signálů. Student dále implementuje některý z modelů neuronových sítí v programovacím jazyce Python a využije jej pro natrénování a následnou simulaci libovolného efektu nebo systému pro úpravu akustického signálu. V rámci semestrální práce vypracujte teoretickou část práce, vytvořte zvukovou databázi pro trénování neuronové sítě a implementujte jednu ze struktur sítí pro modelování zvukového signálu. Neuronové sítě jsou v průběhu posledních let používány stále více, a to víceméně přes celé spektrum vědních oborů. Neuronové sítě založené na architektuře WaveNet a sítě využívající rekurentních vrstev se v současné době používají v celé řadě využití, zahrnující například syntézu lidské řeči, nebo napřklad při metodě "black-box" modelování akustických systémů, které upravují zvukový signál (modulačí efekty, nelineární zkreslovače, apod.). Tato akademická práce si dává za cíl poskytnout úvod do problematiky neuronových sítí, vysvětlit základní pojmy a mechanismy této problematiky. Popsat využití neuronových sítí v modelování akustických systémů a využít těchto poznatků k implementaci neuronových sítí za cílem modelování libovolného efektu nebo zařízení pro úpravu zvukového signálu.
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Research of tempo features comparing audio records
Ištvánek, Matěj ; Galáž, Zoltán (referee) ; Kiska, Tomáš (advisor)
This thesis deals with technical properties of audio signals or more precisely of recordings from the prepared database and describes parameters which are used for music transcription and analysis of audio signals. It summarises information about music theory and automatic transcription of audio recordings, introduces specialist studies that deal with problems of signal analysis and their results. Furthermore it mentions attributes with the best ability to generally differentiate included songs from rhythmical and metrical aspects. Thesis analyses in the MATLAB language, from the prepared database, all interpretations of the piece "String Quartet No. 1 – IV. Con moto" from Leoš Janáček with two selected methods and shows results of the analysis and comparing of the methods. Finally the work summarizes all information and problems of the thesis.
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Universal Audio 1176 Compressor
Pavlik, Miroslav ; Ištvánek, Matěj (referee) ; Koton, Jaroslav (advisor)
The aim of this bachelor thesis is to get acquainted with the issue of analog compressor Universal Audio 1176 and verify the functionality and principles of individual block diagrams of this compressor. The bachelor's thesis is carried out for a detailed analysis of individual blocks of compressor 1176. A practical implementation was constructed, to verify the correct functionality of compressor 1176 on measurements, which were performed in the laboratory.
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Impulse noise detection in audio signals
Hůla, Josef ; Ištvánek, Matěj (referee) ; Mokrý, Ondřej (advisor)
Study disserts known method of detecting impulsive noise in audiosignal. Differential, filtering, autoregressive and ARMA methods are discussed. First, each method is theoretically examined and the character of impulsive disturbances is presented. Later an~implementation of each method is presented and results of their performance is compared. In order to have comparable results, the methods are tested on synthetic impulses with known position and duration and also on recordings containing real impulsive noise.
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Analysis of Expressive Music Performance using Digital Signal Processing Methods
Ištvánek, Matěj ; Mekyska, Jiří (referee) ; Smékal, Zdeněk (advisor)
This diploma thesis deals with methods of the onset and tempo detection in audio signals using specific techniques of digital processing. It analyzes and describes the issue from both the musical and the technical side. First, several implementations using different programming environments are tested. The system with the highest detection accuracy and adjustable parameters is selected, which is then used to test functionality on the reference database. Then, an extension of the algorithm based on the Teager-Kaiser energy operator in the preprocessing stage is created. The difference in accuracy of both systems is compared – the operator has on average increased the accuracy of detection of a global tempo and inter-beat intervals. Finally, a second dataset containing 33 different interpretations of the first movement of Bedřich Smetana’s composition, String Quartet No. 1 in E minor "From My Life". The results show that the average tempo of the entire first movement of the song slightly decreases depending on the later year of the recording.
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A tool for simultaneous playback of multiple composition interpretations
Švejcar, Michael ; Ištvánek, Matěj (referee) ; Miklánek, Štěpán (advisor)
The purpose of this Bachelor’s thesis was to create a piece of software which enables the user to simultaneously play back multiple interpretations of a musical piece and switch between them instantaneously. This was achieved using the App Designer in the MATLAB environment, which is intended for developing applications with graphical user interface. The key to the development of the application was especially the use of available toolboxes and algorithms for computing chromagrams and multiscale dynamic time warping. The final IntSwitcher player enables the user to load two recordings of interpretations of one song. Chromagrams which characterize the individual recordings in terms of tonal development over time are first calculated from the input files. After that, the multiscale dynamic time warping method is applied on the chromagrams, which outputs the warping path. The warping path in this case is a matrix, in which musically corresponding samples of loaded audio files are assigned together with the resolution of 50 ms. From this, the corresponding time position of currently inactive track is computed along with its slider position. If the user switches the currently played recording, the second track starts playing in the same part of composition, even if that part is at a different time in each of the individual recordings. The final software is an appropriate tool for studying differences between various interpretations of the same musical piece.
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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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Tempo detector based on a neural network
Suchánek, Tomáš ; Smékal, Zdeněk (referee) ; Ištvánek, Matěj (advisor)
This Master’s thesis deals with beat tracking systems, whose functionality is based on neural networks. It describes the structure of these systems and how the signal is processed in their individual blocks. Emphasis is then placed on recurrent and temporal convolutional networks, which by they nature can effectively detect tempo and beats in audio recordings. The selected methods, network architectures and their modifications are then implemented within a comprehensive detection system, which is further tested and evaluated through a cross-validation process on a genre-diverse data-set. The results show that the system, with proposed temporal convolutional network architecture, produces comparable results with foreign publications. For example, within the SMC dataset, it proved to be the most successful, on the contrary, in the case of other datasets it was slightly below the accuracy of state-of-the-art systems. In addition,the proposed network retains low computational complexity despite increased number of internal parameters.
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Extraction of parameters for the research of music performance
Laborová, Anna ; Miklánek, Štěpán (referee) ; Ištvánek, Matěj (advisor)
Different music performances of the same piece may significantly differ from each other. Not only the composer and the score defines the listener’s music experience, but the music performance itself is an integral part of this experience. Four parameter classes can be used to describe a performance objectively: tempo and timing, loudness (dynamics), timbre, and pitch. Each of the individual parameters or their combination can generate a unique characteristic performance. The extraction of such objective parameters is one of the difficulties in the field of Music Performance Analysis and Music Information Retrieval. The submitted work summarizes knowledge and methods from both of the fields. The system is applied to extract data from 31 string quartet performances of 2. movement Lento of String Quartet no. 12 F major (1893) by czech romantic composer Antonín Dvořák (1841–1904).
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Web interface for audio feature visualization
Putz, Viliam ; Ištvánek, Matěj (referee) ; Miklánek, Štěpán (advisor)
This thesis deals with methods of audio features extraction from audio files, visualization of these features and implementation of web interface, which provides the visualization. In the introduction, Music Information Retrieval field, with which this thesis is closely related, is described. Also, the current state in the area of applications for audio features extraction is described. Next, the most common libraries for audio feature extraction within the programming languages are listed. In the second chapter, the audio features that can be extracted from audio file are listed and described. In the third chapter, there is description of the process of implementation, used technologies, function diagram of the web interface, explanation of functionality and description of user interface and its functions.
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