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Analysis of impact of noise in recordings on the automated detection of hypokinetic dysarthria
Havelková, Nikola ; Galáž, Zoltán (referee) ; Kováč, Daniel (advisor)
This thesis deals with the automated detection of hypokinetic dysarthria by analysing the influence of noise present in recordings. Appropriate single-channel methods, specifically the spectral subtraction and Kalman filter, are selected and implemented in the MATLAB R2022a to enhance speech. These methods are also used for noise-free recordings, to which additive white noise was added. Afterwards, the effectiveness of these methods is objectively evaluated by using signal-to-noise ratio values. After enhancing of speech, interferences are extracted from the recordings. The effect of the presence of noise, as well as its subsequent suppression by individual methods, is then evaluated by statistical analysis, specifically using the Kruskal-Wallis test and the post hoc Dunn’s test. The probability of distributing parameters of clean, noisy and enhanced recordings, for which the effect of noise is significant, according to statistical tests, are plotted using violin and box graphs. Finally, the classification was done by logistic regression with the help of machine learning, where the effect of the presence of noise and subsequent speech enhancement on automated detection of hypokinetic dysarthria was described according to the area values under the ROC curve.
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Speech Enhancement Methods
Kukučka, Peter ; Mekyska, Jiří (referee) ; Hudec, Antonín (advisor)
Aim of this work is summarize some single-channel methods of speech enhancement. These methods are explained in this work: Basic Spectral Subtraction Method, Modified Spectral Subtraction, Multi-band Spectral subtraction, spectral subtraction MMSE and Wiener filtering. All methods are implemented. Preprocessing, voice activity detector and speech scores are explained in this paper, too.
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Composite Subband Adaptive Speech Enhancement
Hovorka, Jaroslav ; Vlček, Čestmír (referee) ; Křesálek,, Vojtěch (referee) ; Sysel, Petr (advisor)
The thesis deals with single channel and multiple channel algorithms for speech enhancement. The goal of this work is to perform the deep analysis of both single channel and multiple channel algorithms in sense of their behaviour in noisy environment of combat vehicles and platforms. Based on this analysis a new composite speech enhancement algorithm will be designed. This new approach is expected to increase quality of the processed speech in military communications systems. These systems are characterised by their operation under very noisy conditions where background noise is very high and signal-to-noise ratio extremely low. These noisy conditions are typical for the range of military and combat platforms and vehicles.
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System for the support of comparison of algorithms for noise reduction in audiosignal
Bartoš, Jan ; Smékal, Zdeněk (referee) ; Míča, Ivan (advisor)
The main purpose is to create a system for working with audio-signal, which is user-friendly and ready for next expansion. The program is developed in the Qt library of the Linux Ubuntu 7.4 operating system with using of C/C++ language. Another purpose is to demonstrate the functionality of the program on simple channel speech. To this aim there are implemented algorithms of the spectral subtraction and of the spektrogram's tresholding with using of FFT algorithm. The parts of the work are the teoretical part of the GUI implementation and the implementation of denoising methods, a partial description of the program and his structure and instruction manual.
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3D Game in Unity with Music Analysis
Petrjanoš, Jakub ; Chlubna, Tomáš (referee) ; Milet, Tomáš (advisor)
This thesis is about music analysis and it's usage in game development in game engine Unity. With help of music analysis there is implemented path finding in procedural generated terrain. In development were used experimental methods and result is game, which generates path based on chosen song through procedural generated terrain and visualizes music.
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Methods of noise suppression for speech recognition systems
Moldříková, Zuzana ; Smital, Lukáš (referee) ; Odstrčilík, Jan (advisor)
This diploma thesis deals with methods of noise suppression for speech recognition systems. In theoretical part are discussed basic terms of this topic and also methods for noise suppression. These are spectral subtraction, Wiener filtering, RASTA, mapping of spectrogram or algorithms based on noise estimation. In second part types of noise are analyzed, there is proposal and implementation of spectral subtraction method of noise suppression for speech recognition system. Also extensive testing of spectral subtractive algorithms in comparison with Wiener filter is conducted. Assessment of this testing is done with defined metrics, successfulness of recognition, recognition system score and signal to noise ratio.
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Analysis of impact of noise in recordings on the automated detection of hypokinetic dysarthria
Havelková, Nikola ; Galáž, Zoltán (referee) ; Kováč, Daniel (advisor)
This thesis deals with the automated detection of hypokinetic dysarthria by analysing the influence of noise present in recordings. Appropriate single-channel methods, specifically the spectral subtraction and Kalman filter, are selected and implemented in the MATLAB R2022a to enhance speech. These methods are also used for noise-free recordings, to which additive white noise was added. Afterwards, the effectiveness of these methods is objectively evaluated by using signal-to-noise ratio values. After enhancing of speech, interferences are extracted from the recordings. The effect of the presence of noise, as well as its subsequent suppression by individual methods, is then evaluated by statistical analysis, specifically using the Kruskal-Wallis test and the post hoc Dunn’s test. The probability of distributing parameters of clean, noisy and enhanced recordings, for which the effect of noise is significant, according to statistical tests, are plotted using violin and box graphs. Finally, the classification was done by logistic regression with the help of machine learning, where the effect of the presence of noise and subsequent speech enhancement on automated detection of hypokinetic dysarthria was described according to the area values under the ROC curve.
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3D Game in Unity with Music Analysis
Petrjanoš, Jakub ; Chlubna, Tomáš (referee) ; Milet, Tomáš (advisor)
This thesis is about music analysis and it's usage in game development in game engine Unity. With help of music analysis there is implemented path finding in procedural generated terrain. In development were used experimental methods and result is game, which generates path based on chosen song through procedural generated terrain and visualizes music.
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Speech Enhancement Methods
Kukučka, Peter ; Mekyska, Jiří (referee) ; Hudec, Antonín (advisor)
Aim of this work is summarize some single-channel methods of speech enhancement. These methods are explained in this work: Basic Spectral Subtraction Method, Modified Spectral Subtraction, Multi-band Spectral subtraction, spectral subtraction MMSE and Wiener filtering. All methods are implemented. Preprocessing, voice activity detector and speech scores are explained in this paper, too.
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