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Physiological Data to Analyze and Improve the User Experience
Štěpánek, Daniel ; Beran, Vítězslav (referee) ; Materna, Zdeněk (advisor)
The goal of this thesis is to obtain dataset of physiological data for user emotions in order to analyze and improve human-computer interaction. This paper proposes of the use Empatica wristband to capture physiological data and Python for data processing. After evaluation, 94 % of intact data was obtained from the expected number of samples. Based on the obtained data, it is possible to better analyze the user experience and thus improve it.
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Facial expressions of emotions
Zajícová, Markéta ; Bahbouh, Radvan (advisor) ; Boukalová, Hedvika (referee)
Title: Facial Expressions of Emotions Author: Bc. Markéta Zajícová Department: Department of Psychology, Charles University in Prague, Faculty of Arts Supervisor: doc. PhDr. MUDr. Mgr. Radvan Bahbouh, Ph.D. Abstract: The theses is dedicated to facial expressions of emotions, it begins with a brief introduction to the topic of emotions as one of the cognitive functions, there is a definition of the term, classification of emotions and their psychopathology, it briefly summarizes the various theories of emotions. The greater part of the theoretical section is devoted to basic emotions and their manifestation in the face, as well as the ability to recognize and imitate them. The theoretical part is closed by the topic of emotional intelligence as a unifying element that highlights the importance of this issue. Empirical part is primarily focused on two abilities related to facial expressions of emotions, specifically the recognition and the production of them, then links these capabilities with additional characteristics as the gender, the education and their self-estimation. The main finding of this theses is that there is a statistical significant relationship (ρ=0.35, α=0.05) between the emotion recognition and production. Key words: Basic Emotion, Facial Expressions of Emotions, Emotion Recognition,...
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Recognition of Facial Expressions of Emotions
Zajícová, Markéta ; Niederlová, Markéta (referee) ; Lukavský, Jiří (referee)
Title: Recognition of Facial Expressions of Emotions Author: Mgr. Markéta Zajícová Department: Department of Psychology, Charles University in Prague, Faculty of Arts Supervisor: Mgr. Ing. Martin Vraný Abstract: This work addresses the topic of emotion recognition from facial expressions. The theoretical part starts with general information about emotions; the most elaborated part, however, concerns basic emotions and their manifestation. One part of this work is also about the ability to recognize emotions, its deficits, and its methods of measurement. The theoretical part is closed by the topic of emotional intelligence, which is the overarching element. The empirical part focuses on the differences in the ability to recognize emotions. The results show that women are better in emotion recognition than men, similarly psychologists and coaches, unlike patients with a psychotic disorder whose results are sub- normal. The results also suggest the tendency of positive correlation between the level of education and the coveted ability - with increasing education the ability to recognize emotion expressions is improved. Subtle emotions are recognized with more difficulties in the test, but emotions displayed by out-group members are, against the expectations, better recognized. The results are unable to confirm...
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Biological changers of CNS caused by trauma
Maulenová, Kristýna ; Šivicová, Gabriela (advisor) ; Kulišťák, Petr (referee)
This thesis focuses on traumatic brain injury and its negative impact on both the brain as a whole and component brain structures. The first two chapters of the theoretical part summarize the information of the anatomy and functions of central nervous system and the most common causes of traumas and its characteristics. The crucial part of the thesis consists of the psychological consequences of traumas arranged according to brain lobe that plays the major role in a clinical manifestation of impaired functions. The thesis also sums up the field of neurodiagnotics and mentions some concrete methods that are being used when dealing with patients after traumas. The last chapter of the theoretical part deals with possibilities and examples of neurorehabilitation as well as factors which are involved in the prognosis of the posttraumatic condition. A part of this chapter also pays attention to the brain plasticity. The last two chapters in this segment refer to other literature from this field. The empirical part presents the research proposal of changes of the brain parts that are involved in facial emotion recognition among TBI patients. The research tools are Ekman 60 Faces Test and an imaging technique SPECT. Key words: Central nervous system, brain lobes, neurodiagnostics, psychological...
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Emotion Detection from Speech
Popková, Anna ; Fér, Radek (referee) ; Matějka, Pavel (advisor)
This Bachelor Thesis deals with research in the field of emotion recognition mainly from speech and marginally from other modalities (video and physiological data). It closely describes the topology of the systems built specifically for the subject of this work. Moreover, it describes experiments leading to optimized pre-processing, regressor training and post-processing. Data used for these research origins from evaluation AV+EC 2015. Results of fusion systems producing the most precise prediction were sent to this evaluation. The Bottle-Neck features are newly tested and combined favorably with commonly used eGeMAPS features for the recognition of arousal. For valence, two kinds of video features are used. Muli-task system (recognizing both valence and arousal) using Bottle-Neck features produces competitive results and is only 13 % relatively behind the mentioned fusion system. This is especially appealing for applications where only audio is available.
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Convolutional Neural Networks for Emotion Recognition
Jileček, Jan ; Najman, Pavel (referee) ; Hradiš, Michal (advisor)
Convolutional neural networks are used for various tasks, but foremost in machine learning, in which they excel. This work is going to introduce some existing frameworks, other algorithms for recognition and then we describe the training dataset creation and the model for emotion recognition training process. Mentioned model has accuracy of 60%. It is used for emotion statistics retrieval from movie trailers. Model for genre recognition is created from those statistics and then finally used in our application for genre recognition of the input trailer, with best accuracy of 47%.
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Stress recognition from speech signal
Staněk, Miroslav ; Přibil, Jiří (referee) ; Tučková,, Jana (referee) ; Sigmund, Milan (advisor)
Předložená disertační práce se zabývá vývojem algoritmů pro detekci stresu z řečového signálu. Inovativnost této práce se vyznačuje dvěma typy analýzy řečového signálu, a to za použití samohláskových polygonů a analýzy hlasivkových pulsů. Obě tyto základní analýzy mohou sloužit k detekci stresu v řečovém signálu, což bylo dokázáno sérií provedených experimentů. Nejlepších výsledků bylo dosaženo pomocí tzv. Closing-To-Opening phase ratio příznaku v Top-To-Bottom kritériu v kombinaci s vhodným klasifikátorem. Detekce stresu založená na této analýze může být definována jako jazykově i fonémově nezávislá, což bylo rovněž dokázáno získanými výsledky, které dosahují v některých případech až 95% úspěšnosti. Všechny experimenty byly provedeny na vytvořené české databázi obsahující reálný stres, a některé experimenty byly také provedeny pro anglickou stresovou databázi SUSAS.
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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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Emotion Recognition from Acted and Spontaneous Speech
Atassi, Hicham ; Přibil, Jiří (referee) ; Zahradník, Pavel (referee) ; Smékal, Zdeněk (advisor)
Dizertační práce se zabývá rozpoznáním emočního stavu mluvčích z řečového signálu. Práce je rozdělena do dvou hlavních častí, první část popisuju navržené metody pro rozpoznání emočního stavu z hraných databází. V rámci této části jsou představeny výsledky rozpoznání použitím dvou různých databází s různými jazyky. Hlavními přínosy této části je detailní analýza rozsáhlé škály různých příznaků získaných z řečového signálu, návrh nových klasifikačních architektur jako je například „emoční párování“ a návrh nové metody pro mapování diskrétních emočních stavů do dvou dimenzionálního prostoru. Druhá část se zabývá rozpoznáním emočních stavů z databáze spontánní řeči, která byla získána ze záznamů hovorů z reálných call center. Poznatky z analýzy a návrhu metod rozpoznání z hrané řeči byly využity pro návrh nového systému pro rozpoznání sedmi spontánních emočních stavů. Jádrem navrženého přístupu je komplexní klasifikační architektura založena na fúzi různých systémů. Práce se dále zabývá vlivem emočního stavu mluvčího na úspěšnosti rozpoznání pohlaví a návrhem systému pro automatickou detekci úspěšných hovorů v call centrech na základě analýzy parametrů dialogu mezi účastníky telefonních hovorů.
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Recognition of emotions in Czech texts
Červenec, Radek ; Smékal, Zdeněk (referee) ; Burget, Radim (advisor)
With advances in information and communication technologies over the past few years, the amount of information stored in the form of electronic text documents has been rapidly growing. Since the human abilities to effectively process and analyze large amounts of information are limited, there is an increasing demand for tools enabling to automatically analyze these documents and benefit from their emotional content. These kinds of systems have extensive applications. The purpose of this work is to design and implement a system for identifying expression of emotions in Czech texts. The proposed system is based mainly on machine learning methods and therefore design and creation of a training set is described as well. The training set is eventually utilized to create a model of classifier using the SVM. For the purpose of improving classification results, additional components were integrated into the system, such as lexical database, lemmatizer or derived keyword dictionary. The thesis also presents results of text documents classification into defined emotion classes and evaluates various approaches to categorization.
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