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Response of biological signals during acoustic and optical stimulation
Strakoš, Libor ; Chmelař, Milan (referee) ; Bubník, Karel (advisor)
The goal of this thesis is recording and evaluating of biological signals connected with autonomic nervous system. Changes in signals are caused by optical and acoustical stimuli. These stimuli are pictures of different meaning. Colors, basic symbols and neutral pictures with variance in colorization are included. Acoustic stimulation is provided by short startle stimulus of white noise sound impulse. Changes in signals are statistically and subjectively evaluated as changes in emotional state of tested person. Tested people fill in a questionnaire about their feelings. Results of signal processing and questionnaire are compared at the end.
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Linear prediciton and cepstral synthesis of speech signal in the TTS system
Mekyska, Jiří ; Stejskal, Vojtěch (referee) ; Smékal, Zdeněk (advisor)
This work deals with a linear prediction and cepstral synthesis of speech signal in the TTS (Text-to-Speech) systems with the opportunity of modeling the prosody. The work contains a description of speech signal in acoustic and phonetic plane, the principle of speech production and the way we can figure the speech signal in time and frequency domain. Next, there is the TTS block structure mentioned, whereas each block has its own detailed description. In the work, the modeling of prosody using the three most important suprasegmental features (fundamental tone, continuation and speech intensity) is also described. At the end of this work, there is a design and realization of universal Czech TTS system which is based on the speech synthesis in frequency domain. This system is implemented in program MATLAB.
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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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Effect of emotive stimulation in EEG signal
Vaněčková, Tereza ; Ronzhina, Marina (referee) ; Bubník, Karel (advisor)
This thesis deals with emotions and their effect on EEG signal. Firstly, method of electroencephalography, the method of scanning EEG signal, its properties, frequency bands and signal affecting factors are described. The following is an explanation of emotions, its expression, theories of emotion origin, dimensions, classification and lateralization of emotional experience. Furthermore, review of studies that have influenced this work is provided. The practical part consists of the experimental measurement description, principle of stimuli selection, signal EEG recording using the Emotiv EPOC device and the Self-Assessment Manikin evaluation. There are also clarified methods of data processing and selection of emotion related features of EEG signal. The final section summarizes the achieved results and outlines possible continuation of emotional states recognizing.
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Deep Learning for Text Classification
Kolařík, Martin ; Harár, Pavol (referee) ; Povoda, Lukáš (advisor)
Thesis focuses on analysis of contemporary machine learning methods used for text classification based on emotion and testing several deep neural nework architectures. Outcome of this thesis is a neural network architecture, which is tuned for using with text data and which had the best result of 79,94 percent. Proposed method is language independent and it doesn’t require as precisely classified training datasets as current methods. Training and testing datasets were consisted of short amateur movie reviews in Czech and in English. Thesis contains also overview of theoretical basics for convolutional neural networks and history of neural networks and language processing Scripts were written in Python, neural networks were simulated using Keras library and Theano framework. We used CUDA for better performance.
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Response of biological signals on multimedia content
Ondrášková, Lucie ; Chmelař, Milan (referee) ; Bubník, Karel (advisor)
This paper explains the concept of emotion, emotion dimension and how emotions relate to the central nervous system. Additionally, there is research that were the inspiration for this work, the basic types of emotions and their physiological responses. The following are ways to monitor signals caused by emotions. The practical part deals with the sensing signals from the periphery of the body, specifically the EDA, EMG, EOG and PPG. As stimuli to elicit these signals were used photography, music and film. The signals were processed using the program developed in Matlab. Program specific values obtained were statistically analysed.
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Database of vocal samples of human emotions
Hlavica, Michal ; Přinosil, Jiří (referee) ; Atassi, Hicham (advisor)
In this bachelor work is analyzed theory of emotions, how emotions arise and how they are physiologically expressed by human body. How these physiological expressions and emotions reflect into the human speech. Then is described process of creating of speech and basic prosodic and acoustic parameters relevant for research. Theory of creating of databases is described here as well, which is quality ground for database itself. The database is also part of this thesis and they are records cut from television programmes and serials. The next very important issue is description of software tool for subjective evaluating of databases, which was created as a part of this thesis. It was created in C++ language with help by compiler Builder C++ . Also a short analysis of exemplary records for every emotion is done here. This analysis deals with basic frequency, intensity and first three formants.
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Archive+
Šana, Václav ; Hora, Jan (referee) ; Kristek, Jan (advisor)
The proposal deals with the architecture archive concept on a wider social scale. The goal is to treat the information as a certain relative value, when the individual spaces are conceived with emotional surprise. There is a controlled collision between old and new approaches where attractive spaces serve purely rational mechanical systems. A person going through the archive should perceive emotional experiences and, after leaving the archive, perceive information in a more complex way.
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Social Network Analysis using methods of pattern recognition
Križan, Viliam ; Burget, Radim (referee) ; Atassi, Hicham (advisor)
Diplomová práca sa zaoberá rozpoznávaním emócií z textu v sociálnych sieťach. Práca popisuje súčasné metódy extrakcie príznakov, používané lexikóny, korpusy a klasifikátory. Emócie boli rozpoznávané na základe klasifikátoru, netrénovaného na anotovaných dátach z mikroblogovacej siete Twitter. Výhodou použitia služby Twitter, bolo geografické vymedzenie dát, ktoré umožňuje sledovanie zmien emócií populácie v rôznych mestách. Prvým prístupom klasifikácie bolo vytvorenie Baseline algoritmu, ktorý používal jednoduchý lexikón. Pre zlepšenie klasifikácie sme v druhom bode použili komplexnejší SVM klasifikátor. SVM klasifikátory, extrakcie a selekcie príznakov boli použité z dostupnej Python knižnice Scikit. Dáta pre natrénovanie klasifikátoru boli zhromažďované z oblasti USA, a to s pomocou vytvorenej aplikácie. Klasifikátor bol natrénovaný na dátach, označených pri ich zhromažďovaní - bez manuálnej anotácie. Boli použité dve rôzne implantácie SVM klasifikátorov. Výsledné klasifikované emócie, v rôznych mestách a dňoch, boli zobrazené v podobe farebných značiek na mape.
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SW support for emotional state analysis
Lněnička, Jakub ; Míča, Ivan (referee) ; Smékal, Zdeněk (advisor)
The goal of my bachelor work is the description of SW tool with the graphic interface which can be made use of for the purpose of developing the multimodal emotional databases. In its beginning my work deals with the description of the parts of the human body that produce voice (vocal cords) and their functioning. The text is a description of the procedure of transferring the human voice into the digital form where a special attention is paid to the parameters of the speech signal with the emphasis on the description of the symptoms that serve to the purpose of defining the chosen emotions. This work deals with the categorization of emotions and the description of some of them. In the closing part the K-NN classificator is described that serves to the recognition of the individual feelings by means of a produced software.
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