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Web application for speech and voice acquisition
Levák, Adam ; Galáž, Zoltán (referee) ; Mekyska, Jiří (advisor)
This bachelor’s thesis deals with designing and building a web application for speech and voice recording. The main goal of the thesis was to write a theoretical background, create a prototype and build the final web application. The theoretical background involves comparing mobile applications, a comparison of already available solutions for voice and speech recording and an introduction to database systems. The web application prototype was created in an online vector graphics editor Figma. The implementation of the actual web application, which is able to record speech exercises and voice exercises, was written in the JavaScript programming language. The application consists of a set of exercises, specifically picture description, elongated phonation, a diadochokinetic exercise, sentence repetition and text reading. Each exercise will have a text and a voice instruction assisting the user in performing the exercise correctly. Exercise recordings will be safely transferred to an online storage Google Drive. Moreover, a reward system was designed and implemented. It intends to motivate the users to do the exercises regularly, leading to more data collection as these exercises will be done repeatedly. The system is working and tested and is implemented as a progressive web application.
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System of secured actigraph data transfer and processing
Mikulec, Marek ; Galáž, Zoltán (referee) ; Mekyska, Jiří (advisor)
The new Health 4.0 concept brings the idea of combining modern technologies from field of science and technology with research in healthcare and medicine. This work realizes a system of secured actigraph data transfer and preprocessing based on the concept of Health 4.0. The system is successfully designed, implemented, tested and secured. With the help of a non-invasive method of monitoring the movement and temperature of the subject using the GENEActiv actigraph allows the system to securely transfer, process and evaluate the subject's sleep data using the machine learning algorithm XGBoost. The proposed system is in accordance with the valid law of the Czech Republic and meets legal requirements.
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Calculation of speech rate
Galáž, Zoltán ; Smékal, Zdeněk (referee) ; Mekyska, Jiří (advisor)
his semestral thesis deals with a design of system for calculating the rate of speech. The sys-tem consists of several block, such as signal pre-processing block and its segmentation into smaller parts, block of the feature calculation, block of the feature vector quantization and finally block calculating the actual rate. The first step is a change of the input speech signal into a form suitable for the feature extraction. In next step these features are assigned to the calculated centroids. The change of centroid means change of phonemes. The system will record the following boundaries of fonems contained in speech and calculates its rate.
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Detection of the voice fundamental frequency
Chloupek, Jiří ; Mekyska, Jiří (referee) ; Sysel, Petr (advisor)
This bachelor thesis deals with the detection of the pitch man. The frequency of the basic tone is one of the basic parameters of speech signal in the frequency domain. In this thesis we describe several methods for pitch detection and practical application of correlation method and cepstral analysis.
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Analysis of phonation in patients with Parkinson's disease
Kopřiva, Tomáš ; Smékal, Zdeněk (referee) ; Mekyska, Jiří (advisor)
This work deals with analysis of phonation in patients with Parkinson’s disease (PD). Approximately 90% of patients with Parkinson’s disease suffer from speech motor dysfunction called hypokinetic dysarthria. System for Parkinson’s disease analysis from speech signals is proposed and several types of features are examined. Czech Parkinson’s speech database called PARCZ is used for classification. This dataset consists of 84 PD patients and 49 healthy controls. Results are evaluated in two ways. Firstly, features are individually analysed by Spearman correlation, mutual information and Mann-Whitney U test. Classification is based on random forests along with leave-one-out validation. Secondly, SFFS algorithm is employed for feature selection in order to get the best classification result. Proposed system is tested for each gender individually and both genders together as well. Best result for both genders together is expressed by accuracy 89,47 %, sensitivity 91,67% and specificity 85,71 %. Results of this work showed that the most important vowel realizations for phonation analysis are sustained vowels pronounced with maximum or minimum intensity (not whispering).
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Research of new online handwriting features in children with graphomotor difficulties
Gavenčiak, Michal ; Mekyska, Jiří (referee) ; Zvončák, Vojtěch (advisor)
In the Czech Republic, there is currently no objective method to diagnose graphomotor difficulties in children. Ongoing research uses modern digitizers to capture the hand-writing process and quantify its parameters. The first goal of this thesis is to develop software tools to faciliate work with the collected data, such as database validation and writing exercise rating, done by specialists. Another goal of this thesis is to design new on-line handwriting parameters which are then to be analysed on a cohort of school children from 2nd to 4th class of primary school (n=239). The implementation of two desktop programs on the .NET platform is described, among three new quantifying parameters based on the principles of isochrony, two-dimensional cross-correlation, and geometrical centroid. All three parameters show significant correlation (r = [0,2; 0,3])with the HPSQ-C rating in 2nd- and 4th-graders and correlation (𝜌= [0,2; 0,5]) with specialist’s subjective scores in all children from the cohort. The analysis suggests children with graphomotor difficulties struggle with regulating handwriting speed and working memory.
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Assessing movement of articulatory organs based on acoustic analysis of speech
Novotný, Kryštof ; Galáž, Zoltán (referee) ; Mekyska, Jiří (advisor)
Hypokinetic dysarthria is a motor speech disorder often present during Parkinson’s disease. It affects the speech system, including articulatory abilities. There are several speech parameters describing this domain, so it is suggested to deal with their mutual comparison. This work aims to design and describe an algorithm for calculating the parameters of articulation, adapted for the Czech language, and then compare their discriminative power. The acoustic analysis of speech included in it is done via the Praat program and basic machine learning algorithms such as Expectation-Maximization, Kmeans and linear regression are used for the subsequent data processing. The Mann-Whitney U test and representatives of linear, nonlinear and ensemble machine learning models using cross-validation and balanced accuracy are used for evaluation. The results are scripts for automatic assessment of vowel space area, for calculating articulation parameters and for their evaluation. The outputs of the analysis of two different databases (PARCZ and CoBeN) prove that differences in articulation can indeed be observed between normal and dysarthric speech. Based on the mutual comparison of results, it is therefore proposed in the work which parameters and models of machine learning are being appropriate for further dealing with this issue.
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Analysis of the seismic velocity field
Kratochvíl, Pavel ; Mekyska, Jiří (referee) ; Smékal, Zdeněk (advisor)
Seismic velocities are an important prerequisite for seismic processing as a method for hydrocarbons accumulations detection. Seismic velocities are often displayed for mutual comparing, improvement checking, they are filtrated and recalculated for its different characteristic determination. This work deals with basic seismic propagation laws, the meaning of velocities in different stages of seismic processing and this theoretical background is followed by a proposition of method for calculating and displaying of stack velocities.
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Biomedical data visualization using Matlab
Zvončák, Vojtěch ; Mekyska, Jiří (referee) ; Galáž, Zoltán (advisor)
The thesis deals with the visualization of biomedical data in MATLAB environment. The thesis contains following statistical methods and their descriptions: P-P plot, Q-Q plot, histogram, box plot, kernel denstity estimation, scatter plot and several time series metrics. Some functions are programmed from buil-in functions of MATLAB and others using external functions, which are changed to fit to this thesis’s purpose. First part of the thesis conserns theoretical background, whereas the second part conserns practical programmed realizations of mentioned functions. The program contains a graphical user interface - GUI, which the thesis describes in detail. The purpose of the GUI is to ensure ease of use and also data processing. The output graphs of GUI are shown in chapter 5. The last part deals with the possible extensions of the program.
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Detection of Pilot Inattention
Novotný, Josef ; Mekyska, Jiří (referee) ; Smékal, Zdeněk (advisor)
This master thesis deals with the issue of pilot inattention and proposes a design of a system for detecting inattention of general aviation pilots. Inattention belongs to one of the human-caused errors that currently contribute to the most common causes of aviation accidents. The theoretical part deals with the definition of inattention, compares different aviation categories based on flight rules, and contains a search of detection methods. The practical part of the work deals with the selection of suitable sensors, data collection, and implementation of detection algorithms. In this thesis, two different approaches were chosen. The first implementing machine learning using the RUSBoost classifier, which detects states of attention and distraction. The second approach represents the design of a system for detecting pilot inattention based on a set of rules specified in the CLIPS expert system.
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