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Design of signals for nonlinear system modeling
Kuba, Michael ; Ištvánek, Matěj (referee) ; Miklánek, Štěpán (advisor)
This Master’s thesis is focused on training signals for nonlinear system modeling using deep learning. A theoretical introduction to the problem is described, including an initial description of signals and nonlinear distortion audio effects. The goal of the thesis is to design a set of artificial training signals for creating models of distortion guitar effects or tube guitar amplifiers. The designed set of artificial training signals is then processed, utilizing guitar and bass guitar effects, and using a recurrent neural network their models are trained. The quality of the resulting models is afterwards compared with the quality of the models trained with the help of a reference training signal, composed of electric guitar recordings, and signals from commercially available devices. The comparison is carried out in accordance to objective metrics and with subjective evaluation by the MUSHRA listening test.
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Software implementation of the subjective assessments of sound quality
Špeta, Marek ; Balík, Miroslav (referee) ; Rášo, Ondřej (advisor)
The focus of this diploma thesis is on methods for the subjective assessment of sound quality according to recommandations given by International Telecommunication Union ITU. The thesis is thematically divided into four parts. The first part is an interpretation of methods based on internationally accepted standards (method of small impairments, MUSHRA, general methods). The second part describes the functional blocks of application developed for this thesis in LabVIEW enviroment. Next part explains its practical application, especially its running possibilities. The last part describes a listening experiment, aim of which was to verify the application's features and to compare the results of the subjective method used in the experiment with the results of the objective method PEAQ.
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Modern methods of reconstruction of saturated signals
Beránek, Šimon ; Smékal, Zdeněk (referee) ; Rajmic, Pavel (advisor)
This master's thesis deals with the problems of signal degradation caused by clipping and methods for its removal and signal restoration. Basics of mathematical formulations needed, signal processing and optimalization tasks are described. The goal of this thesis is the implementation of basic algorithms used for hard declipping and creating an audio database later used for testing these algorithms. These implementations are followed by modeling of soft clipping and later restored using the improved algorithms. The restorations are tested using the subjective hearing test MUSHRA and the results are statistically evaluated.
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Software implementation of the subjective assessments of sound quality
Špeta, Marek ; Balík, Miroslav (referee) ; Rášo, Ondřej (advisor)
The focus of this diploma thesis is on methods for the subjective assessment of sound quality according to recommandations given by International Telecommunication Union ITU. The thesis is thematically divided into four parts. The first part is an interpretation of methods based on internationally accepted standards (method of small impairments, MUSHRA, general methods). The second part describes the functional blocks of application developed for this thesis in LabVIEW enviroment. Next part explains its practical application, especially its running possibilities. The last part describes a listening experiment, aim of which was to verify the application's features and to compare the results of the subjective method used in the experiment with the results of the objective method PEAQ.
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