Персона: Тихомирова, Дарья Валерьевна
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Институт интеллектуальных кибернетических систем
Цель ИИКС и стратегия развития - это подготовка кадров, способных противостоять современным угрозам и вызовам, обладающих знаниями и компетенциями в области кибернетики, информационной и финансовой безопасности для решения задач разработки базового программного обеспечения, повышения защищенности критически важных информационных систем и противодействия отмыванию денег, полученных преступным путем, и финансированию терроризма.
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Дарья Валерьевна
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- ПубликацияОткрытый доступSocial–Emotional Conversational Agents Based on Cognitive Architectures and Machine Learning(2024) Dolgikh,A.A.; Samsonovich,A.V.; Tikhomirova,D.V.; Долгих, Анатолий Андреевич; Самсонович, Алексей Владимир; Тихомирова, Дарья Валерьевна
- ПубликацияТолько метаданныеEmpirical and modeling study of emotional state dynamics in social videogame paradigms(2020) Tikhomirova, D. V.; Chubarov, A. A.; Samsonovich, A. V.; Тихомирова, Дарья Валерьевна; Самсонович, Алексей Владимир© 2019The objective of this work was to study the dynamics of human emotional states in the process of social interaction in a virtual environment. The previously developed for this purpose prototypes of the virtual actor (NPC) and its virtual environment simulator “Teleport” underwent significant re-design and modification. The experimental platform was re-implemented and used in experiments with college student participants, combining electromyography, emotion recognition in facial recordings and model-based game log analysis in a social videogame paradigm. Participants interacted with two virtual actors implemented based on the eBICA cognitive architecture (Samsonovich, 2013, 2018). Positive correlations were found between eBICA model predictions and participant affects extracted from their facial expressions and facial muscle activity. Affective dynamics of social phenomena, such as the establishment of partnership or an act of betrayal, were characterized and found consistent with the model predictions. Other findings include a gradually developing emotional reaction, possibly due to the integration of appraisals of game events. Overall, obtained results confirm the eBICA model, suggesting its further extension and refinement.
- ПубликацияТолько метаданныеDeep Learning for Effective Visualization and Classification of Recyclable Material Labels(2024) Kuzevanov, V. O.; Tikhomirova, D. V.; Тихомирова, Дарья Валерьевна
- ПубликацияОткрытый доступRecognition of emotions in verbal messages based on neural networks(2021) Malova, I. S.; Tikhomirova, D. V.; Тихомирова, Дарья Валерьевна© 2020 Elsevier B.V.. All rights reserved.Emotion detection and recognition by text is an under-researched area of natural language processing (NLP), which can provide valuable input in various fields. Speech and Emotion Recognition (Speech Emotion Recognition SER) has potentially wide applications, such as interaction with robots, banking, call centers, car onboard systems, computer games, etc.
- ПубликацияОткрытый доступDeep Learning for Effective Visualization and Classification of Recyclable Material Labels(НИЯУ МИФИ, 2024) Kuzevanov, V. O.; Tikhomirova, D. V.; Тихомирова, Дарья ВалерьевнаThis paper presents an example of a system to improve the process of sorting recyclables by using deep learning techniques to automatically detect, classify and visualize recycling codes on product packages. In this paper, the authors discuss various approaches to optical character recognition and object detection in a video stream or image. The authors have developed and proposed a combination of neural networks for detection and classification of recycling codes. The proposed neural network system is designed to facilitate efficient recycling processes by automating the identification of recycling symbols, thereby facilitating the sorting and processing of recyclables.
- ПубликацияТолько метаданныеMapping Action Units to Valence and Arousal Space Using Machine Learning(2024) Gadzhiev, I. M.; Makarov, A. S.; Tikhomirova, D. V.; Dolenko, S. A.; Samsonovich, A. V.; Гаджиев, Исмаил Маратович; Тихомирова, Дарья Валерьевна; Самсонович, Алексей Владимир
- ПубликацияТолько метаданныеToward a general believable model of human-analogous intelligent socially emotional behavior(2020) Samsonovich, A. V.; Chubarov, A. A.; Tikhomirova, D. V.; Eidln, A. A.; Самсонович, Алексей Владимир; Тихомирова, Дарья Валерьевна© Springer Nature Switzerland AG 2020.Social virtual actors need to interact with users emotionally, convincing them in their ability to understand human minds. For this to happen, an artificial emotional intelligence is needed, capable of believable behavior in real-life situations. Summarizing recent work of the authors, the present paper extends the general state-of-the-art framework of emotional AGI, using the emotional Biologically Inspired Cognitive Architecture (eBICA) as a basis. In addition to appraisals, other kinds of fluents are added to the model: somatic markers, feelings, emotional biases, moods, etc. Their integration is achieved on the basis of semantic maps and moral schemas. It is anticipated that this new level of artificial general socially emotional intelligence will complement the next-generation AGI, helping it to merge into the human society on equal with its human members.
- ПубликацияТолько метаданныеThe Contact Cycle for Modeling the Behavior of the Virtual Bot-Presenter(2022) Tikhomirova, D. V.; Тихомирова, Дарья Валерьевна© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.During the development of the Virtual Convention Center (VCC) platform for conferences and while modeling the social-emotional behavior of the platform’s built-in virtual bot-presenter, the question arose about the dynamics of emotions that the presentation bot should express verbally and non-verbally during the presentation in order to interest the listener. In order to model the socio-emotional behavior of a virtual bot-presenter, it is necessary to study the behavior of a human presenter. This paper proposes that the focus of attention in answering this question is not on the speaker and his style of presentation, but on the speaker’s interaction with the listener. In this paper we show that the contact cycle model, known in psychology, is applicable to the speaker-listener relationship and can be used to model the behavior of a virtual bot-presenter and be embedded in its cognitive cycle.
- ПубликацияОткрытый доступVirtual Listener: A Turing-like test for behavioral believability(2020) Chubarov, A. A.; Tikhomirova, D. V.; Shirshova, A. V.; Veselov, N. O.; Samsonovich, A. V.; Тихомирова, Дарья Валерьевна; Самсонович, Алексей Владимир© 2020 The Authors. Published by Elsevier B.V.Virtual Listener (VL) is a generalized prototype of a virtual character based on the principles of cognitive architecture eBICA, which uses facial expressions and body language (eyes movements, head rotation) to keep social and emotional contact with the user. Such contact also implies that VL needs to perceive user's facial expression and gaze, and in the long term- A lso intonation of the user's voice, the sentiment and content of user's speech. In this work, we present an approach to modeling a perceptive 3D virtual listener with emotional capabilities. The virtual character has a 3D face that performs real-time, realistic and believable facial expression dynamics. Our primary goal in this study was to evaluate the concept: E.g., to find out whether a virtual-agent-generated behavior can engender feelings of rapport in human speakers comparable to those that a real human listener can cause? At the same time, this article serves a limited purpose and only describes our current progress so far in addressing this question.
- ПубликацияТолько метаданныеThe Loop of Nonverbal Communication Between Human and Virtual Actor: Mapping Between Spaces(2021) Vladimirov, R. D.; Dolenko, S. A.; Shirokiy, V. R.; Tikhomirova, D. V.; Samsonovich, A. V.; Широкий, Владимир Романович; Тихомирова, Дарья Валерьевна; Самсонович, Алексей Владимир© 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.There is a question about the appropriate emotional and expressive language of a virtual actor. In this paper we study facial expressions. We investigate the transformations between the space of Action Units and the standard affective space in the loop of nonverbal communication between a person and a virtual actor using facial expressions [1]. We are mapping both dimensions into each other using various machine learning algorithms. Action Units space was mapped into emotional space directly using artificial neural networks. Emotional space was mapped into Action Units space with help of dimensionality reduction followed by clusterization of the latter. After the final synthesis, the facial expression of virtual actor can be determined.