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Web applications supporting education of audio signal processing
Malcher, Tomáš ; Mokrý, Ondřej (referee) ; Rajmic, Pavel (advisor)
This bachelors thesis deals with a creation of web applications using JavaScript language. These web applications should be helpful in signal processing classes by showing and explaining different phenomenons to students. Students can see how different parameters affect the outcome of said issue. The theory needed for understanding and implementation is covered by this thesis. Thesis covers key parts of the code of said web applications and the libraries used for their implementaition.
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Restoration of degraded audiosignals using sparse representations
Mokrý, Ondřej ; Veselý, Vítězslav (referee) ; Rajmic, Pavel (advisor)
This bachelor thesis is focused on the problem of inpainting a segment of missing samples in an audiosignal. The signal is represented as sparse vector using discrete Gabor transform. The problem of inpainting missing samples while preserving the sparsity of the representation is formulated as an optimisation task, which is then solved using Douglas-Rachford algorithm. In contrast with the state-of-the-art approaches, the algorithm is extended by proposing method for compensating the energy decrease which occurs in the restored signal.
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Modern methods of reconstruction of saturated audio signals
Mikulášková, Aneta ; Mokrý, Ondřej (referee) ; Rajmic, Pavel (advisor)
This thesis presents a variety of soft clipping simulations and their respective de-clipping functions. A restoration method uses a Douglas-Rachford algorithm (already verified for hard de-clip). The algorithm is extended by inverse functions and simultaneous de-quantization is proposed. The simulations are applied to artificial signals, and audio samples, and the proposal is tested in the computing environment MATLAB. A restored signal is later evaluated by objective and subjective methods.
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Interactive web applications supporting education of 3D graphics
Morávek, Jan ; Mokrý, Ondřej (referee) ; Rajmic, Pavel (advisor)
This diploma thesis is focused on computer 3D graphics and the implementation of educational applications in JavaScript language. Discussed topics of computer graphics include object transformations, Bezier patches and the role of the camera in the scene. The thesis describes the basic theory of these areas and educational applications. The thesis also includes the detailed description of the features and the implementation of the created applications. In the end of the thesis possible extensions are discussed.
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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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Modern methods for restoration of degraded audiosignals
Mokrý, Ondřej ; Koldovský,, Zbyněk (referee) ; Rajmic, Pavel (advisor)
The master's thesis deals with the problem of restoring a block of missing samples in a digital audio signal. This problem is formulated as an optimization task, which seeks the sparsest time-frequency representation of a signal within the set of feasible reconstructed signals. Several particular formulations are discussed, namely the analyzing and the synthesizing model, both for convex and non-convex approaches. Suitable algorithms are proposed for solving these formulations, and in the convex case, the method is further enhanced by various procedures to compensate for the energy drop in the inpainted signal segment. The proposed algorithms are tested on real recordings, and their performance is shown to be competitive with the state-of-the-art.
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Restoration of missing audio signal samples using a psychoacoustic model
Švento, Michal ; Záviška, Pavel (referee) ; Mokrý, Ondřej (advisor)
This bachelor thesis deals with the reconstruction of short-time damaged audio signal. The signal is represented by sparse signal representation using discrete Gabor transform. Convex optimalization tools are used for the reconstruction. The optimalization problem is solved using the Douglas—Rachford and Chambolle—Pock algorithm. Psychoacoustic model is involved in algorithm to obtain better results in objective metrics. The comparison is realised by an objective method SDR, PEMO-Q and also subjectively.
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Restoration of damaged audio signals using autoregressive models
Soboňa, Matúš ; Rajmic, Pavel (referee) ; Mokrý, Ondřej (advisor)
The bachelor thesis deals with the problem of restoring audio signals damaged by sample loss, using autoregressive models. The restoration itself is solved by W. Etter and A. Janssen's algorithms. These algorithms are implemented in MATLAB and tested on artificial signals aswell as on real recordings. Algorithms are then compared based on quality of restoration dependent on different parameters of signals.
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Audio signal denoising using deep learning
Pacal, Tomáš ; Záviška, Pavel (referee) ; Mokrý, Ondřej (advisor)
This thesis deals with noise removal in audio signal using deep learning. The basic types of neural networks and their use in audio signal processing are described. The possibilities of implementing neural networks are tested in Matlab and Python. Subsequently, a~convolutional neural network model is proposed, according to which four different convolutional network architectures are implemented and then trained and tested on different types of noise. Based on these tests, one architecture was selected and subjected to a comparative test on a speech recording and then on a music recording, together with a noise reduction method using wavelet transform. The results are evaluated using both objective sound quality metrics and an informal listening test. The neural network achieved better results according to all the metrics used as well as in the listening test.
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Increasing bit depth in audio signals
Mrázek, Tomáš ; Mokrý, Ondřej (referee) ; Rajmic, Pavel (advisor)
The task of this bachelor’s thesis is to get acquainted with basic and advanced dequantization methods. It describes basics of declipping with focus on method which uses social sparsity. From this method, an audio dequantization algorithm using social sparsity can be designed and implemented. The resulting program automatically quantize the original file to the required bit depth and then reconstruct it to the closest possible resemblance to the original.
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