View in EDS

Virtual companionship : Intelligent custom companionship software

Saved in:
Bibliographic Details
Title: Virtual companionship : Intelligent custom companionship software
Authors: Song, Simin
Publication Year: 2025
Collection: Theseus.fi (Open Repository of the Universities of Applied Sciences / Ammattikorkeakoulujen julkaisuarkisto)
Subject Terms: fi=Tieto- ja viestintätekniikka|sv=Informations- och kommunikationsteknik|en=Information and Communications Technology, Android, chatbots, Python (programming languages), programming, personality, SQLite, software technology, Degree Programme in Information Technology
Description: Loneliness has been identified as a predictor of depression in people, especially in adolescents, with communication recognized as a potential means to alleviate feelings of loneliness. The ad-vent of large language model (LLM) chat systems has enabled the development of robots capable of engag-ing in conversations with individuals at any time and place. This study presents the creation of a chatbot system designed to dynamically adjust its conversational style based on the 16 personality types of the My-ers-Briggs Type Indicator (MBTI). By utilizing fine-tuning techniques for large language models, the system adapts its responses and tone to align with the selected personality type, offering users a personalized and engaging interaction. The system was implemented using Python Flask for the backend, incorporating fine-tuned language models to facilitate natural language processing, and the frontend Android application was developed in Java to provide a user-friendly interface. The evaluation results indicate that the chatbot effectively mirrors per-sonality-specific traits within conversations.
Document Type: bachelor thesis
Language: English
Relation: https://www.theseus.fi/handle/10024/888983
Availability: https://www.theseus.fi/handle/10024/888983
Rights: fi=All rights reserved. This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.|sv=All rights reserved. This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.|en=All rights reserved. This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.|
Accession Number: edsbas.9B147AD7
Database: BASE
Description
Abstract:Loneliness has been identified as a predictor of depression in people, especially in adolescents, with communication recognized as a potential means to alleviate feelings of loneliness. The ad-vent of large language model (LLM) chat systems has enabled the development of robots capable of engag-ing in conversations with individuals at any time and place. This study presents the creation of a chatbot system designed to dynamically adjust its conversational style based on the 16 personality types of the My-ers-Briggs Type Indicator (MBTI). By utilizing fine-tuning techniques for large language models, the system adapts its responses and tone to align with the selected personality type, offering users a personalized and engaging interaction. The system was implemented using Python Flask for the backend, incorporating fine-tuned language models to facilitate natural language processing, and the frontend Android application was developed in Java to provide a user-friendly interface. The evaluation results indicate that the chatbot effectively mirrors per-sonality-specific traits within conversations.