Evaluation of Neural-Network and Large-Language Model Approaches for Generating Instructions for Animations

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dc.contributor.authorBARLETTARO, ELISABETTA
dc.contributor.authorERIKSSON, EMMA
dc.contributor.departmentChalmers tekniska högskola / Institutionen för fysiksv
dc.contributor.departmentChalmers University of Technology / Department of Physicsen
dc.contributor.examinerMehlig, Bernhard
dc.contributor.supervisorFröjd, Martin
dc.date.accessioned2025-02-13T14:48:28Z
dc.date.available2025-02-13T14:48:28Z
dc.date.issued2025
dc.date.submitted
dc.description.abstractConversational agents are used more and more in customer service, health care, for educational purposes. The fundamental problems of conversational agents are many, including limitations in interpretation of complex queries and lack of emotional intelligence. Despite this, there are distinct advantages of conversational agents, such as efficient data analysis, reduction of operational costs and aid in interactive learning for personalized teaching. The most significant challenge this project aims to undertake is to generate realistic and complex animations in the context of interactive learning with a real-time constraint. The investigation includes how to select machine learning tools and models to aid in the advancement of animation generation, by using both Large-Language Models and purposely constructed Neural Networks. While Large-Language Models are convenient when used in straightforward conditions, Neural Networks are more dependable in an operative application thanks to their consistent format, adaptability and specifically developed purpose.
dc.identifier.coursecodeTIFX05
dc.identifier.urihttp://hdl.handle.net/20.500.12380/309126
dc.language.isoeng
dc.setspec.uppsokPhysicsChemistryMaths
dc.subjectanimations, armature, avatar, Blender, blendshapes, educational, largelanguage models, neural networks, Python, real-time, training simulator, Unity
dc.titleEvaluation of Neural-Network and Large-Language Model Approaches for Generating Instructions for Animations
dc.type.degreeExamensarbete för masterexamensv
dc.type.degreeMaster's Thesisen
dc.type.uppsokH
local.programmeComplex adaptive systems (MPCAS), MSc
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