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Chatbot Based on Artificial Neural Networks
Červíček, Petr ; Novotný, Ondřej (referee) ; Szőke, Igor (advisor)
The thesis pursues the implementation of the chatbot based on neural networks. It uses Long short term memory networks, which remember long-term dependencies. Chatbot was implemented in Python with superstructure Keras and is based on sequence-to-sequence. Chatbot was also tested by BLEU and given to users, who chatted with the chatbot. For a better understanding of the given problematics, there is simple description of the chatbot history and used technologies.
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Modelling Emotions in Communication Agents
Sivák, Martin ; Černocký, Jan (referee) ; Smrž, Pavel (advisor)
This work deals with current chatterbot systems. It describes problems and possibilities of improvement with emphasis on natural language processing and emotion modeling during conversation. There is an implementation, based on the described knowledge, introduced in the second part of the thesis, also with experimental success rate evaluation.
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Human-like conversations with Digital Personas: Conversational strategies that support mutual understanding
Kunc, Benjamín ; Šipošová, Barbora (advisor) ; Nováková Schöffelová, Miroslava (referee)
Communication is a collaborative process, and as such requires the communicators to create common ground - the assumption that they mutually understand each other on a sufficient level (Clark, 1996). The AI-powered virtual agents capable of using natural language to communicate with humans have recently attracted the attention of both the general public and experts, as the progress enables humans to give virtual agents more complex tasks in which a conversation itself is a crucial part of a task, such as in education, healthcare or mental health. While the virtual agents are getting better at understanding natural language, their ability to fulfill complex independent tasks (conducting semi-structured interviews, tutoring, coaching, etc.) is bounded by the limitations of their communication skills, and thus they perform the best at rather short, domain-specific conversations (Drouin et al., 2022). The goals of this thesis were to 1) create an experimental framework designed for a brief (5min) social voice chat between humans and virtual agents that would allow to experimentally manipulate different conversational strategies; 2) propose the first set of conversational strategies for mutual understanding and suggest appropriate self-report and behavioral metrics to measure the impact of the...
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Social Network Discourse - Facebook, the Virtual Community
Lešková, Zuzana ; Kraus, Jiří (advisor) ; Trampota, Tomáš (referee)
Social Network Discourse - Facebook, the Virtual Community - Abstract Rigorous thesis "Social Network Discourse - Facebook, the Virtual Community" endeavours to study the social network discourse on its contextual level. When using various perspectives, the concrete analysis of such disourse focuses on particular virtual interactions within their thematical and conversational scope.
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Chatbot Based on Artificial Neural Networks
Červíček, Petr ; Novotný, Ondřej (referee) ; Szőke, Igor (advisor)
The thesis pursues the implementation of the chatbot based on neural networks. It uses Long short term memory networks, which remember long-term dependencies. Chatbot was implemented in Python with superstructure Keras and is based on sequence-to-sequence. Chatbot was also tested by BLEU and given to users, who chatted with the chatbot. For a better understanding of the given problematics, there is simple description of the chatbot history and used technologies.
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Social Network Discourse - Facebook, the Virtual Community
Lešková, Zuzana ; Kraus, Jiří (advisor) ; Trampota, Tomáš (referee)
Social Network Discourse - Facebook, the Virtual Community - Abstract Rigorous thesis "Social Network Discourse - Facebook, the Virtual Community" endeavours to study the social network discourse on its contextual level. When using various perspectives, the concrete analysis of such disourse focuses on particular virtual interactions within their thematical and conversational scope.
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