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Recognition of Objects in Pictures
Nedoma, David ; Samek, Jan (referee) ; Zbořil, František (advisor)
This thesis is about solving a problem of recognition of objects in pictures. The aim was to create a program that will be able to recognize objects in an image. Describes progressively step by step processing of image data. Shortly describes preprocessing of image, after that describes in detail segmentation, description of segmented data and classification of objects. Describes algorithms and methods that are applicable for each step.
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Stress Evaluation, Coping and Reduction
Bohatcová, Tereza ; Otavová, Jana (referee) ; Franková, Emilie (advisor)
Master's thesis deals with the stress applied to the employee in a work process in the company ABC, Ltd. It focuses on the factors that cause stress. It examines its manifestations and effects on health and work performance of employees. The theoretical part includes an overview of this issue. The practical part is analytical, processing questionnaires students - future employees and current employees. Visions of students at secondary and university level of stress that occurs in the process, are compared to the fact how stress manifests itself directly to employees in working conditions. The conclusion presents proposals to reduce or eliminate stress and increase resilience against him.
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Stress Evaluation, Coping and Reduction
Kršková, Božena ; Müller, Svatopluk (referee) ; Franková, Emilie (advisor)
The Master’s thesis "Stress evaluation, coping and reduction" dealing with the currently very topical issue the stress acting on employee working conditions. It analyzes the types of stress, signs, symptoms and effects on health and work performance of employees. The thesis is focused on the factors causing stress, their identification and reduction of the company. The theoretical part is focused on theoretical analysis of the problems. The practical part is devoted to the measurement of stressors in the working environment for catering JHREST s.r.o. employees. The work conclusion includes a proposal of the stress factors reduction in the company.
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Comparison of analysis of speech in dependence on age and gender
Báňa, Josef ; Smékal, Zdeněk (referee) ; Atassi, Hicham (advisor)
This thesis deals with analysis of speech signal in dependence on the gender and the age of the speaker. We tried to investigate through the features to find the best set for the automatic classification of speakers. It also contains a brief discussion about the speech signal and its characteristics. We used a program called Praat for the speech analysis purpose. This program is also described in this work. We mainly focused on the suprasegmental features of speech. Our first step was to make our own speech corpus which should contain speech records from speakers with various age and gender. We made the analysis using Praat and reported it within this thesis. For the automatic classification purpose, twelve features were selected basing on there quality criteria and used with a neural network to classify the speakers to classes with different age and gender. As it was mentioned, a neural network was used as a classifier. We used “Neural Network Toolbox” in the Matlab program to create and train our networks.
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Determining person's height from spoken utterance
Pelikán, Pavel ; Mekyska, Jiří (referee) ; Atassi, Hicham (advisor)
Diploma’s thesis is focused on determining person’s height from spoken utterance. First part of the work evaluates present situation and refers to the published studies. Knowledge gained in these studies was used in this thesis. Study with the best results according to estimated height of the speakers was chosen. The experiment realized in the chosen study was performed in this work. The system for the estimation of the height of the speakers based on the speech signal was created. This system was successfully tested by using several acoustic features on spoken utterances from TIMIT database.
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Emotional State Recognition and Classification Based on Speech Signal Analysis
Černý, Lukáš ; Atassi, Hicham (referee) ; Smékal, Zdeněk (advisor)
The diploma thesis focuses on classification of emotions. Thesis deals about parameterization of sounds files by suprasegment and segment methods with regard for next used of these methods. Berlin database is used. This database includes many of sounds records with emotions. Parameterization creates files, which are divided to two parts. First part is used for training and second part is used for testing. Point of interest is self-organization network. Thesis includes Matlab´s program which can be used for parameterization of any database. Data are classified by self-organization network after parameterization. Results of hits rates are presented at the end of this diploma thesis.
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Paralinguistic signals recognition in spoken dialogs
Mašek, Jan ; Míča, Ivan (referee) ; Atassi, Hicham (advisor)
This document describes the three methods for the detection and classification of paralinguistic expressions such as laughing and crying from usual speech by analysis of the audio signal. The database of records was originally designed for this purpose. When analyzing everyday dialogs, music might be included, so the database was extended by four new classes as speech, music, singing with music and usual speech with background music. Feature extraction, feature reduction and classification are common steps in recognizing for all three methods. Difference of the methods is given by classification process in detail. One classification of all six classes at once is proposed in the first method called straight approach. In the second method called decision tree oriented approach we are using five intuitive sub classifiers in the tree structure and the final method uses for classification emotion coupling approach. The best features were reduced by feature evaluation using F-ratio and GMM classifiers were used for the each classification part.
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Emotional State Recognition Based on Speech Signal Analysis
Čermák, Jan ; Atassi, Hicham (referee) ; Smékal, Zdeněk (advisor)
The thesis is focused on the emotional states classification in the Matlab program, using neural networks and the classifier which is based on a combination of Gaussian density functions. It deals with the speech signal processing; the prosodic and spectral signs and the MFCC coefficients were extracted from the signal. The work also deals with the quality evaluation of individual signs of which the most suitable were chosen in order to provide the correct classification of emotional states. In order to identify the emotional states, two different methods were used. The first method of classification was the use of neural networks with differently selected parameters, and the second method was the use of the Gaussian mixture model (GMM). In both methods, a database of emotional utterances was divided into the training group and the test group. The testing was based on a method independent of the speaker. The work also includes the comparison of individual analyzed methods as well as the representation and comparison of the results. The conclusion comprises a proposition for the best parameters and the best classifier for the recognition of the speaker’s emotional state.
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Burnout
Woitsch, Marek ; Franková, Emilie (advisor) ; Honsová, Pavlína (referee)
This thesis deals with the issue of burnout. The work is divided into two parts. The theoretical part defines the concepts of burnout, its risks, symptoms, stages and treatment. The second part deals with research in gastronomy and in the helping professions through MBI questionnaire. Its aim is to determine the level of burnout of the sample according to gender, age group and length of practice. Results analyze and determine which group is more vulnerable.
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