PersonaX: Your Digital Reflection

The rapid advancement of Artificial Intelligence (AI) and Machine Learning (ML) has enabled the creation of highly interactive virtual assistants capable of understanding human emotions and context. This paper presents AI Twin, an intelligent, emotion-aware, and personalized desktop assistant designed to replicate human-like communication, adaptive learning, and dynamic memory. Unlike traditional AI chatbots that provide static responses, AI Twin utilizes Retrieval-Augmented Generation (RAG), dynamic prompt conditioning, and emotion-based personality mapping to deliver contextual, human-like conversations. The system integrates modules from Machine Learning (ML), Artificial Intelligence (AI), Data Science (DSBDA), and Database Management Systems (DBMS) to manage memory, user profiles, and behavioral learning. The AI Twin architecture consists of a multimodal interface supporting voice, text, and video interac- tion. It also includes a control panel and progress dashboard for user monitoring and model control. Through dynamic context retrieval and daily memory updates, the assistant continuously learns from user interactions, maintaining a personalized conversational identity. Experimental analysis demonstrates enhanced contextual accuracy, emotional adaptability, and user engagement compared to conventional assistant systems. The AI Twin project contributes to the evolution of digital companionship and adaptive human–AI collaboration

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Publication Details

Journal
International Journal of Advanced Research in Science Communication and Technology
Published
2025-10-14
DOI
https://doi.org/10.48175/ijarsct-29878
Primary Topic
Persona Design and Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

PersonaX: Your Digital Reflection

T. Arivanantham, Shaikh Sohel, Salgar Hariom, Shaikh Bushara et al.
International Journal of Advanced Research in Science Communication and Technology
Persona Design and Applications
article

PersonaX: Your Digital Reflection

T. Arivanantham, Shaikh Sohel, Salgar Hariom, Shaikh Bushara, Wagchaure Abhijit
article en

Abstract

The rapid advancement of Artificial Intelligence (AI) and Machine Learning (ML) has enabled the creation of highly interactive virtual assistants capable of understanding human emotions and context. This paper presents AI Twin, an intelligent, emotion-aware, and personalized desktop assistant designed to replicate human-like communication, adaptive learning, and dynamic memory. Unlike traditional AI chatbots that provide static responses, AI Twin utilizes Retrieval-Augmented Generation (RAG), dynamic prompt conditioning, and emotion-based personality mapping to deliver contextual, human-like conversations. The system integrates modules from Machine Learning (ML), Artificial Intelligence (AI), Data Science (DSBDA), and Database Management Systems (DBMS) to manage memory, user profiles, and behavioral learning. The AI Twin architecture consists of a multimodal interface supporting voice, text, and video interac- tion. It also includes a control panel and progress dashboard for user monitoring and model control. Through dynamic context retrieval and daily memory updates, the assistant continuously learns from user interactions, maintaining a personalized conversational identity. Experimental analysis demonstrates enhanced contextual accuracy, emotional adaptability, and user engagement compared to conventional assistant systems. The AI Twin project contributes to the evolution of digital companionship and adaptive human–AI collaboration

International Journal of Advanced Research in Science Communication and Technology
Dr. D. Y. Patil Medical College, Hospital and Research Centre (IN)
Openalex Percentile: Top 65%
Persona Design and Applications
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