Relevant bibliographies by topics / Emotion Models

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Emotion Models'

Author: Grafiati
Published: 4 June 2021
Last updated: 31 January 2023

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Journal articles on the topic "Emotion Models"

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Thornton, Mark A., and Diana I. Tamir. "Mental models accurately predict emotion transitions." Proceedings of the National Academy of Sciences 114, no. 23 (2017): 5982–87. http://dx.doi.org/10.1073/pnas.1616056114.

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Successful social interactions depend on people’s ability to predict others’ future actions and emotions. People possess many mechanisms for perceiving others’ current emotional states, but how might they use this information to predict others’ future states? We hypothesized that people might capitalize on an overlooked aspect of affective experience: current emotions predict future emotions. By attending to regularities in emotion transitions, perceivers might develop accurate mental models of others’ emotional dynamics. People could then use these mental models of emotion transitions to pred
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Fathalla, Rana. "Emotional Models." International Journal of Synthetic Emotions 11, no. 2 (2020): 1–18. http://dx.doi.org/10.4018/ijse.2020070101.

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Emotion modeling has gained attention for almost two decades now due to the rapid growth of affective computing (AC). AC aims to detect and respond to the end-user's emotions by devices and computers. Despite the hard efforts being directed to emotion modeling with numerous tries to build different models of emotions, emotion modeling remains an art with a lack of consistency and clarity regarding the exact meaning of emotion modeling. This review deconstructs the vagueness of the term ‘emotion modeling' by discussing the various types and categories of emotion modeling, including computationa
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Mehta, Ansh. "Emotion Detection using Social Media Data." International Journal for Research in Applied Science and Engineering Technology 9, no. 11 (2021): 1456–59. http://dx.doi.org/10.22214/ijraset.2021.39027.

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Abstract: Previous research on emotion recognition of Twitter users centered on the use of lexicons and basic classifiers on pack of words models, despite the recent accomplishments of deep learning in many disciplines of natural language processing. The study's main question is if deep learning can help them improve their performance. Because of the scant contextual information that most posts offer, emotion analysis is still difficult. The suggested method can capture more emotion sematic than existing models by projecting emoticons and words into emoticon space, which improves the performan
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Vuoskoski, Jonna K., and Tuomas Eerola. "Measuring music-induced emotion." Musicae Scientiae 15, no. 2 (2011): 159–73. http://dx.doi.org/10.1177/1029864911403367.

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Most previous studies investigating music-induced emotions have applied emotion models developed in other fields to the domain of music. The aim of this study was to compare the applicability of music-specific and general emotion models – namely the Geneva Emotional Music Scale (GEMS), and the discrete and dimensional emotion models – in the assessment of music-induced emotions. A related aim was to explore the role of individual difference variables (such as personality and mood) in music-induced emotions, and to discover whether some emotion models reflect these individual differences more s
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Vuoskoski, Jonna K., and Tuomas Eerola. "Measuring Music-Induced Emotion: A Comparison of Emotion Models, Personality Biases, and Intensity of Experiences." Musicae Scientiae 15, no. 2 (2011): 159–73. http://dx.doi.org/10.1177/102986491101500203.

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Most previous studies investigating music-induced emotions have applied emotion models developed in other fields to the domain of music. The aim of this study was to compare the applicability of music-specific and general emotion models – namely the Geneva Emotional Music Scale (GEMS), and the discrete and dimensional emotion models – in the assessment of music-induced emotions. A related aim was to explore the role of individual difference variables (such as personality and mood) in music-induced emotions, and to discover whether some emotion models reflect these individual differences more s
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He, Jing-Xian, Li Zhou, Zhen-Tao Liu, and Xin-Yue Hu. "Digital Empirical Research of Influencing Factors of Musical Emotion Classification Based on Pleasure-Arousal Musical Emotion Fuzzy Model." Journal of Advanced Computational Intelligence and Intelligent Informatics 24, no. 7 (2020): 872–81. http://dx.doi.org/10.20965/jaciii.2020.p0872.

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In recent years, with the further breakthrough of artificial intelligence theory and technology, as well as the further expansion of the Internet scale, the recognition of human emotions and the necessity for satisfying human psychological needs in future artificial intelligence technology development tendencies have been highlighted, in addition to physical task accomplishment. Musical emotion classification is an important research topic in artificial intelligence. The key premise of realizing music emotion classification is to construct a musical emotion model that conforms to the character
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Cahyani, Denis Eka, and Irene Patasik. "Performance comparison of TF-IDF and Word2Vec models for emotion text classification." Bulletin of Electrical Engineering and Informatics 10, no. 5 (2021): 2780–88. http://dx.doi.org/10.11591/eei.v10i5.3157.

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Emotion is the human feeling when communicating with other humans or reaction to everyday events. Emotion classification is needed to recognize human emotions from text. This study compare the performance of the TF-IDF and Word2Vec models to represent features in the emotional text classification. We use the support vector machine (SVM) and Multinomial Naïve Bayes (MNB) methods for classification of emotional text on commuter line and transjakarta tweet data. The emotion classification in this study has two steps. The first step classifies data that contain emotion or no emotion. The second st
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Hudlicka, Eva. "Guidelines for Designing Computational Models of Emotions." International Journal of Synthetic Emotions 2, no. 1 (2011): 26–79. http://dx.doi.org/10.4018/jse.2011010103.

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Rapid growth in computational modeling of emotion and cognitive-affective architectures occurred over the past 15 years. Emotion models and architectures are built to elucidate the mechanisms of emotions and enhance believability and effectiveness of synthetic agents and robots. Despite the many emotion models developed to date, a lack of consistency and clarity regarding what exactly it means to ‘model emotions’ persists. There are no systematic guidelines for development of computational models of emotions. This paper deconstructs the often vague term ‘emotion modeling’ by suggesting the vie
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Bruna, O., H. Avetisyan, and J. Holub. "Emotion models for textual emotion classification." Journal of Physics: Conference Series 772 (November 2016): 012063. http://dx.doi.org/10.1088/1742-6596/772/1/012063.

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Zhang, Yong De, Shu Tong Li, Jin Gang Jiang, and Tian Hua He. "Research on Emotion Body Language Model of the Humanoid Robot." Applied Mechanics and Materials 494-495 (February 2014): 1278–81. http://dx.doi.org/10.4028/www.scientific.net/amm.494-495.1278.

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In order to improve the personification of human-robot emotion interaction, this paper based on the Euclidean space emotion model and Ekman theory of emotion, deduces the general formula of emotion characteristic value, establishes a improvement model of robot which can express the robots emotion through the body language. The general formula of emotional feature value make the models suitable for the expression of various emotions, and through body language to express the emotions, improves the emotion expression model generality and adaptability.
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Dissertations / Theses on the topic "Emotion Models"

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Lewis, Suzanne Carole. "Computational models of emotion and affect." Thesis, University of Hull, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.417166.

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Mignault, Alain. "Connectionist models of the perception of facial expressions of emotion." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape10/PQDD_0019/NQ55360.pdf.

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Mignault, Alain 1962. "Connectionist models of the perception of facial expressions of emotion." Thesis, McGill University, 1999. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=36039.

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Two connectionist models are developed that predict humans' categorization of facial expressions of emotion and their judgements of similarity between two facial expressions. For each stimulus, the models predict the subjects' judgement, the entropy of the response, and the mean response time (RT). Both models involve a connectionist component which predicts the response probabilities and a response generator which predicts the mean RT. The input to the categorization model is a preprocessed picture of a facial expression, while the hidden unit representations generated by the first model for
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Deng, Jie. "Emotion-based music retrieval and recommendation." HKBU Institutional Repository, 2014. https://repository.hkbu.edu.hk/etd_oa/82.

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The digital music industry has expanded dramatically during the past decades, which results in the generation of enormous amounts of music data. Along with the Internet, the growing volume of quantitative data about users (e.g., users’ behaviors and preferences) can be easily collected nowadays. All these factors have the potential to produce big data in the music industry. By utilizing big data analysis of music related data, music can be better semantically understood (e.g., genres and emotions), and the user’s high-level needs such as automatic recognition and annotation can be satisfied. F
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Gray, Wesley Barclay. "A discursive study of models of emotion in teaching and learning science." Thesis, University of Canterbury. School of Sciences and Physical Education, 2010. http://hdl.handle.net/10092/4654.

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The purpose of this study is to uncover the principles that inform a teacher’s dialogic behaviour, and shape her feelings, and to understand the implications of these principles for multiple aspects of pedagogic practice. I investigate the principles that underpin an emotional practice for two teachers, Julia and Lydia, and their Year 10 science lower band learners. Towards this goal, I approach the theory and empirical data in this study in ways that create opportunities for researching teachers’ emotions that other approaches do not: I examine patterns, commonality and relationships across c
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Read, Harriet. "Music, emotion and auditory processing : towards new models of musical expression and cognition." Thesis, University of Sheffield, 2001. http://etheses.whiterose.ac.uk/15061/.

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This study represents an interdisciplinary investigation of music cognition from both theoretical and empirical perspectives drawing principally from research in neuropsychology, and philosophy. The main aim of the thesis is to produce a coherent model of music cognition, reconciling empirical findings, current accounts of musical expression, and broader cognitive models. With this aim the investigation divides into two parts: first, examining musical expression of emotion, and second, exploring music cognition as a whole and its place within global models of cognition. A particular focus is t
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Zhang, Yang. "Intelligent emotion recognition from facial and whole-body expressions using adaptive ensemble models." Thesis, Northumbria University, 2015. http://nrl.northumbria.ac.uk/23588/.

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Automatic emotion recognition has been widely studied and applied to various computer vision tasks (e.g. health monitoring, driver state surveillance, personalized learning, and security monitoring). With the great potential provided by current advanced 3D scanners technology (e.g. the Kinect), we shed light on robust emotion recognition based one users’ facial and whole-body expressions. As revealed by recent psychological and behavioral research, facial expressions are good in communicating categorical emotions (e.g. happy, sad, surprise, etc.), while bodily expressions could contribute more
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Laws, Sheena Elizabeth. "Emotion perception in early childhood : relations with attachment security and internal working models." Thesis, Durham University, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.505881.

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Fortes, Neto Amyr Borges. "Giving emotional contagion ability to virtual agents in Crowds." Pontif?cia Universidade Cat?lica do Rio Grande do Sul, 2017. http://tede2.pucrs.br/tede2/handle/tede/7769.

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Christensen, Kara Alise. "Examining relationships between interpersonal emotion regulation, psychopathology, andrelationship quality in female friend dyads." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1563803675071968.

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Books on the topic "Emotion Models"

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Haug, Marc, and Richard E. Whalen, eds. Animal models of human emotion and cognition. American Psychological Association, 1999. http://dx.doi.org/10.1037/10335-000.

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Yang, Yi-Hsuan. Music emotion recognition. CRC, 2011.

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H, Chen Homer, ed. Music emotion recognition. CRC, 2011.

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The three dimensions of stuttering: Neurology, behavior, and emotion. PRO-ED, 1991.

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The three dimensions of stuttering: Neurology, behavior, and emotion. 2nd ed. Whurr Publishers Ltd, 1999.

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Development of emotions and emotion regulation: An internalization model. Springer Science, 2006.

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Karandashev, Victor. Cultural Models of Emotions. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-58438-2.

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Plutchik, Robert, and Hope R. Conte, eds. Circumplex models of personality and emotions. American Psychological Association, 1997. http://dx.doi.org/10.1037/10261-000.

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Robert, Plutchik, and Conte Hope R. 1929-, eds. Circumplex models of personality and emotions. American Psychological Association, 1997.

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Sánchez-Escribano, M. Guadalupe. Engineering Computational Emotion - A Reference Model for Emotion in Artificial Systems. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-59430-9.

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Book chapters on the topic "Emotion Models"

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Gu, Xiaosi. "Computational models of emotion." In The Routledge Handbook of the Computational Mind. Routledge, 2018. http://dx.doi.org/10.4324/9781315643670-33.

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Holland, Dorothy, and Andrew Kipnis. "American Cultural Models of Embarrassment." In Everyday Conceptions of Emotion. Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-015-8484-5_10.

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Hudlicka, Eva. "From Habits to Standards: Towards Systematic Design of Emotion Models and Affective Architectures." In Emotion Modeling. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12973-0_1.

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Pfeifer, Rolf. "Artificial Intelligence Models of Emotion." In Cognitive Perspectives on Emotion and Motivation. Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-009-2792-6_12.

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Brizard, Bruno. "Animal and Human Models of Startle, Emotion, and Depression." In Surprise: An Emotion? Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-98657-9_4.

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Petta, Paolo. "Emotion Models for Situated Normative Systems?" In Deontic Logic and Artificial Normative Systems. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11786849_3.

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Roesch, Etienne B. "Editorial: “Theories and Models” of Emotion." In Cognitive Technologies. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15184-2_1.

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Ortony, Andrew. "Subjective Importance and Computational Models of Emotions." In Cognitive Perspectives on Emotion and Motivation. Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-009-2792-6_13.

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Javed, Nazura, and B. L. Muralidhara. "Emotions During Covid-19: LSTM Models for Emotion Detection in Tweets." In Proceedings of the 2nd International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-6407-6_13.

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García, Hernán F., Mauricio A. Álvarez, and Álvaro Orozco. "Gaussian Process Dynamical Models for Emotion Recognition." In Advances in Visual Computing. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-14364-4_77.

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Conference papers on the topic "Emotion Models"

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G. Ho, Amic. "Exploring the Role of Emotion in the Design Cycle." In Applied Human Factors and Ergonomics Conference. AHFE International, 2021. http://dx.doi.org/10.54941/ahfe100583.

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Scholars have focused on “design and emotion” for more than a decade. Various studies, models, and theories have been proposed and adopted to explore the relationship between design and emotion, and to explain how emotion can be applied in the design process. After the theories are categorised according to the respective focuses, three main components that influence or are influenced by emotion can be identified: designers, design outcome and users or consumers in the design cycle. Based on the relationships amongst these components, numerous similar terms categorised under emotion and design
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Giżycka, Barbara, and Grzegorz J. Nalepa. "Emotion in Models Meets Emotion in Design: Building True Affective Games." In 2018 IEEE Games, Entertainment, Media Conference (GEM). IEEE, 2018. http://dx.doi.org/10.1109/gem.2018.8516439.

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Tabatabaei, S. S., M. J. Yazdanpanah, M. S. Tavazoei, and A. Karimian. "On dynamic models of human emotion." In 2012 20th Iranian Conference on Electrical Engineering (ICEE). IEEE, 2012. http://dx.doi.org/10.1109/iraniancee.2012.6292476.

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Zhao, Weixiang, Yanyan Zhao, and Xin Lu. "CauAIN: Causal Aware Interaction Network for Emotion Recognition in Conversations." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/628.

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Emotion Recognition in Conversations has attained increasing interest in the natural language processing community. Many neural-network based approaches endeavor to solve the challenge of emotional dynamics in conversations and gain appealing results. However, these works are limited in capturing deep emotional clues in conversational context because they ignore the emotion cause that could be viewed as stimulus to the target emotion. In this work, we propose Causal Aware Interaction Network (CauAIN) to thoroughly understand the conversational context with the help of emotion cause detection.
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Savery, Richard, and Gil Weinberg. "A Survey of Robotics and Emotion: Classifications and Models of Emotional Interaction." In 2020 29th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN). IEEE, 2020. http://dx.doi.org/10.1109/ro-man47096.2020.9223536.

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Salari, Soorena, Amin Ansarian, and Hajar Atrianfar. "Robust emotion classification using neural network models." In 2018 6th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS). IEEE, 2018. http://dx.doi.org/10.1109/cfis.2018.8336626.

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Lv, Guoyun, Shuixian Hu, Yangyu Fan, and Min Qi. "Visual emotion recognition based on dynamic models." In 2013 IEEE International Conference on Signal Processing, Communications and Computing. IEEE, 2013. http://dx.doi.org/10.1109/icspcc.2013.6664137.

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Dhaouadi, Sabrine, Hedi Abdelkrim, and Slim Ben Saoud. "Speech Emotion Recognition: Models Implementation & Evaluation." In 2019 International Conference on Advanced Systems and Emergent Technologies (IC_ASET). IEEE, 2019. http://dx.doi.org/10.1109/aset.2019.8871014.

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Gund, Manasi, Abhiram Ravi Bharadwaj, and Ifeoma Nwogu. "Interpretable Emotion Classification Using Temporal Convolutional Models." In 2020 25th International Conference on Pattern Recognition (ICPR). IEEE, 2021. http://dx.doi.org/10.1109/icpr48806.2021.9412134.

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Nogueiras, Albino, Asunción Moreno, Antonio Bonafonte, and José B. Mariño. "Speech emotion recognition using hidden Markov models." In 7th European Conference on Speech Communication and Technology (Eurospeech 2001). ISCA, 2001. http://dx.doi.org/10.21437/eurospeech.2001-627.

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Reports on the topic "Emotion Models"

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Gratch, Jonathan, and Stacy Marsella. Evaluating a Computational Model of Emotion. Defense Technical Information Center, 2006. http://dx.doi.org/10.21236/ada459183.

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Yatsymirska, Mariya. MODERN MEDIA TEXT: POLITICAL NARRATIVES, MEANINGS AND SENSES, EMOTIONAL MARKERS. Ivan Franko National University of Lviv, 2022. http://dx.doi.org/10.30970/vjo.2022.51.11411.

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The article examines modern media texts in the field of political journalism; the role of information narratives and emotional markers in media doctrine is clarified; verbal expression of rational meanings in the articles of famous Ukrainian analysts is shown. Popular theories of emotions in the process of cognition are considered, their relationship with the author’s personality, reader psychology and gonzo journalism is shown. Since the media text, in contrast to the text, is a product of social communication, the main narrative is information with the intention of influencing public opinion
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Osadchyi, Viacheslav V., Hanna B. Varina, Kateryna P. Osadcha, et al. The use of augmented reality technologies in the development of emotional intelligence of future specialists of socionomic professions under the conditions of adaptive learning. CEUR Workshop Proceedings, 2020. http://dx.doi.org/10.31812/123456789/4633.

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In modern conditions, innovative augmented reality technologies are actively developing, which are widespread in many areas of human activity. Introduction of advanced developments in the process of professional training of future specialists of socionomic professions in the conditions of adaptive training, contributes to the implementation of the principles of a personalized approach and increase the overall level of competitiveness. The relevant scientific article is devoted to the theoretical and empirical analysis result of conducting a psychodiagnostic study on an innovative computer comp
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Killgore, William D. A Model for Predicting Cognitive and Emotional Health from Structural and Functional Neurocircuitry Following Traumatic Brain Injury. Defense Technical Information Center, 2014. http://dx.doi.org/10.21236/ada610795.

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Killgore, William D., Mareen Weber, and Maia Kipman. A Model for Predicting Cognitive and Emotional Health from Structural and Functional Neurocircuitry Following Traumatic Brain Injury. Defense Technical Information Center, 2013. http://dx.doi.org/10.21236/ada610919.

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Osadcha, Kateryna, Viacheslav Osadchyi, Serhiy Semerikov, Hanna Chemerys, and Alona Chorna. The Review of the Adaptive Learning Systems for the Formation of Individual Educational Trajectory. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/4130.

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The article is devoted to the review of the adaptive learning systems. We considered the modern state and relevance of usage of the adaptive learning systems to be a useful tool of the formation of individual educational trajectory for achieving the highest level of intellectual development according to the natural abilities and inclination with the help of formation of individual trajectory of education, the usage of adaptive tests for monitoring of the quality of acquired knowledge, the formation of complicated model of the knowledge assessment, building of the complicated model of the subje
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Bayley, Stephen, Darge Wole Meshesha, Paul Ramchandani, Pauline Rose, Tassew Woldehanna, and Louise Yorke. Socio-Emotional and Academic Learning Before and After COVID-19 School Closures: Evidence from Ethiopia. Research on Improving Systems of Education (RISE), 2021. http://dx.doi.org/10.35489/bsg-rise-wp_2021/082.

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This paper presents the findings of research undertaken in Ethiopia to examine the effects of COVID-19 school closures on children’s holistic learning, including both socio-emotional and academic learning. It draws on data collected in 2019 (prior to the pandemic) and 2021 (after schools reopened) to compare primary pupils’ learning before and after the school closures. In particular, the study adapts self-reporting scales that have been used in related contexts to measure Grade 3 and 6 children’s social skills, self-efficacy, emotional regulation and mental health and wellbeing, along with li
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Бережна, Маргарита Василівна. Psycholinguistic Image of Joy (in the Computer-Animated Film Inside Out). Psycholinguistics in a Modern World, 2021. http://dx.doi.org/10.31812/123456789/5827.

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The paper is focused on the correlation between the psychological archetype of a film character and the linguistic elements composing their speech. The Nurturer archetype is represented in the film Inside Out by the personalized emotion Joy. Joy is depicted as an antropomorphous female character, whose purpose is to keep her host, a young girl Riley, happy. As the Nurturer, Joy is completely focused on Riley’s happiness, which is expressed by lexico-semantic group ‘happy’, positive evaluative tokens, exclamatory sentences, promissive speech acts, and repetitions. She needs the feeling of conne
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Халік, Олена Олександрівна. Особливості образів батьківської та майбутньої сімейної системи у сучасних студентів жіночої статі та їх взаємозв’язок з рівнем перфекціонізму. Гнозис, 2015. http://dx.doi.org/10.31812/123456789/3791.

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У статті аналізуються особливості образів батьківської та майбутньої сімейних систем у сучасних студентів жіночої статі, визначаються збалансованість та незбалансованість вказаних родин. З’ясовано, що третина образів майбутньої родини є незбалансованими, з домінуванням заплутано-хаотичного типу. Встановлено зв’язок перфекціонізму спрямованого на інших та соціально обумовленого перфекціонізму з окремими показниками образу майбутньої сім’ї. This article deals with the analyze of the female students’ perceptions of their parental family and their own future family systems. Author determines the b
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10

Lylo, Taras. Ideologemes of modern Russian propaganda in Mikhail Epstein’s essayistic interpretations. Ivan Franko National University of Lviv, 2022. http://dx.doi.org/10.30970/vjo.2022.51.11404.

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The article analyzes the main anti-propaganda accents in Mikhail Epstein’s essayistic argumentation about such messages of modern Russian propaganda as “Russia is threatened by an external enemy”, “Russia is a significant, powerful country”, “The collapse of the USSR was a tragedy”, “Russia is a special spiritual civilization”, “Our cause in Donbass is sacred”, “The enemy uses, or may use of illegal weapons”... A special emphasis is placed on the fact that the basis of these concepts is primarily ontological rather than ideological. Ideology is rather a cover for problematic Russian existence
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