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Reconstruction of signal modified by fade-in/fade-out
Bača, Petr ; Kiska, Tomáš (referee) ; Rajmic, Pavel (advisor)
This thesis contains the theory needed to solve the special problem of bit-depth expansion. The goal is to reconstruct the signal which suffered from application of the fade-in, fade-out effect. The theory includes information of analog to digital conversion and the theory of sparse representations. Thesis formulates the task of bit-depth expansion and advices the algorithm to solve it. Furthermore, the realization of the issue is discussed and the results are given.
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An alternative JPEG coder/decoder
Jirák, Jakub ; Kiska, Tomáš (referee) ; Rajmic, Pavel (advisor)
The JPEG codec is currently the most widely used image format. This work deals with the design and implementation of an alternative JPEG codec using proximal algorithms in combination with the fixation of points from the original image to suppression of artifacts created in common JPEG coding. To solve the problem, the prox_TV and then the Douglas-Rachford algorithm were used, for which special functions using l_1-norm for image reconstruction were derived. The results of the proposed solution are very good because they can effectively suppress the artefacts created and the result corresponds to the image with a higher set qualitative factor. The proposed method achieves very good results for both simple images and photos, but in the case of large images (1024 × 1024 px) and larger, a large amount of computing time is required, so the method is more suitable for smaller images.
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Application for the calculation of speech features describing hypokinetic dysarthria
Hynšt, Miroslav ; Mekyska, Jiří (referee) ; Kiska, Tomáš (advisor)
This thesis is about design and implementation of application for computing speech parameters on people with Parkinson disease. At the beginning is generaly described Parkinson disease and Hypokinetic dysarthria and how it affects the speech and speech parameters when it occurs. Mainly there are described areas of speech like phonation, prosody, articulation and fluent speech. As a part of next topic this thesis describes specific speech parameters with bigger meaning during diagnosis Parkinson disease and it's progress over the time. There are also mentioned few significant studies dealing with examination of speech of the subjects with diagnoses of Parkinson disease and computing some speech parameters in order to analyze their speech impairments. Part of the thesis is description of implemented standalone application for calculating, exporting and visualizing of speech parameters from selected sound records.
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Platform for subjective evaluation of video-sequences
Srnec, Tomáš ; Kiska, Tomáš (referee) ; Číka, Petr (advisor)
This bachelor thesis is focused on subjective video quality assessment. Used modern codecs such as H.264, H.265, VP8 and VP9 are described in first chapter. In the next part of the thesis, four methods of the subjective video assessment are being called, according to Recommendation ITU-T P.910. The practical part includes encoding of three videos, into four resolutions, for four codecs. Output of the thesis is JavaFX application, capable of playing used videos for participants of test, who are making judgment. Their results are real-time sent to MySQL server and directly in application evaluated into bar charts. According to our results, the best codec is VP9, before codec H.265, H.264 and VP8.
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Acoustic analysis of gender-related patterns in Parkinson's disease
Herinek, Denis ; Kiska, Tomáš (referee) ; Galáž, Zoltán (advisor)
The bachelor's thesis is about acoustic analysis of gender-related patterns in Parkinson's disease by analysing speech task: reading passage. Parkinson's disease manifests in all subsystems involved in speech production (respiration, phonation, articulation and prosody). The aim of this thesis is familirization with symptoms of this disorder and speech parameters influenced by this disorder. Thesis contains preprocessing, parametrization of speech signal and statistic analysis of parameters. System of speech signal processing is created in MATLAB programming language.
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De-identification of speakers with hypokinetic dysarthria
Kárník, Radoslav ; Kiska, Tomáš (referee) ; Mekyska, Jiří (advisor)
This paper discuses design and implementation of a system that performs de-identification of speech recordings of patients suffering from Parkinson's disease. The paper describes causes and symptoms of Parkinson's disease and effects of hypokinetic dysarthria on speech. Part of the paper is devoted to speech features that can be used for diagnosing hypokinetic dysarthria from speech. It also describes ways of speech de-identification and system for evaluating results using recognition of speakers and patients. De-identification system uses vocal tract length normalization (VTLN) and evaluating system uses Gaussian mixture models (GMM). PARCZ database was used for testing. It contains recordings of speech of patients affected by Parkinson's disease and control speakers.
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Image codecs based on the wavelet transform
Kiska, Tomáš ; Říha, Kamil (referee) ; Rajmic, Pavel (advisor)
This bachelor´s thesis describes issues of wavelet compression, which is today already in common use mainly at work with digital photographs or other pictures. Using these algorithm you can copy informations and save efficiently. There are main image formats and types of compression suitable for editing pictures desribed in this thesis. So the focus is on discrete wavelet transform, which uses so-called wavelets, the Haar´s and Daubechies wavelet are the best known of all. Next chapter of this work explores colour spaces, in which can be a picture displayed. In case of coding and encoding it is model RGB and YCbCr. Not least there is mentioned term of picture decomposition. At the end, there are image codecs EZW, SPITH and EBCOT which are describe in detail.
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Degree of Parkinson's disease estimation based on acoustic analysis of speech
Ustohalová, Iveta ; Kiska, Tomáš (referee) ; Galáž, Zoltán (advisor)
The diploma thesis deals with the non-invasive analysis of progression of Parkinson´s disease using the acoustic analysis of speach. Hypokinetic dysarthria in connection with Parkinson´s disease as well as speech parameters are described in this work. Speech parameters are sorted according to the speech component they affect. The work uses the phonation of vowels "a" speech task as the most commonly used speech task in the field of pathological speech processing, because of its resistance to demographic and linguistic characteristics of the speakers. Based on obtained knowledge, in MATLAB development enviroment were created systém for UPDRS III scale estimation. The UPDRS III scale is based on subjective diagnosis given by the doctor. At first, one individual parameter is used for the UPDRS III scale value estimation. Then the feature selection using SFFS algorithm is applied to gain feature combination with minimal estimation errror. Attention i salso paid to correlation between individual symptoms and UPDSR III scale.
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Acoustic analysis of sentences complicated for articulation in patients with Parkinson's disease
Kiska, Tomáš ; Smékal, Zdeněk (referee) ; Mekyska, Jiří (advisor)
This work deals with a design of hypokinetic dysarthria analysis system. Hypokinetic dysarthria is a speech motor dysfunction that is present in approx. 90 % of patients with Parkinson’s disease. Next there is described Parkinson's disease and change of the speech signal by this disability. The following describes the symptoms, which are used for the diagnosis of Parkinson's disease (FCR, VSA, VAI, etc.). The work is mainly focused on parameterization techniques that can be used to diagnose or monitor this disease as well as estimate its progress. A protocol of dysarthric speech acquisition is described in this work too. In combination with acoustic analysis it can be used to estimate a grade of hypokinetic dysarthria in fields of faciokinesis, phonorespiration and phonetics (correlation with 3F test). Regarding the parameterization, new features based on method RASTA. The analysis is based on parametrization sentences complicated for articulation. Experimental dataset consists of 101 PD patients with different disease progress and 53 healthy controls. For classification with feature selection have selected method mRMR.
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