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A Literature Survey on Personalized AI-Based Voice Assistant for Authentication

Manjunath M S1, Hemanth K2, Tanmay Raj3  Prashanth J4

1Department of Information science and Engineering, Global Academy of Technology,Bangalore

2Department of Information science and Engineering, Global Academy of Technology,Bangalore

3Department of Information science and Engineering, Global Academy of Technology,Bangalore

4Department of Information science and Engineering, Global Academy of Technology,Bangalore

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Abstract - This literature review critically examines the evolving landscape of personalized AI-based voice assistants in the realm of authentication services, The review begins with an exploration of the development and nuanced functionalities of voice recognition technologies, emphasizing their integration in multi-factor authentication systems. It delves into the synergistic relationship between voice and facial recognition technologies, highlighting advancements and challenges in biometric authentication, including accuracy, user experience, and security vulnerabilities.A significant focus is placed on the role of AI in personalizing user interactions with authentication services, where adaptive learning and contextual awareness are pivotal.The review also addresses the enduring relevance of traditional security measures, such as secure PIN’s, and their interplay with biometric methods to fortify authentication processes.The economic and commercial implications of these technologies are explored, considering their impact on business models and market trends.This comprehensive review identifies gaps in the current research landscape and suggests potential directions for future inquiry, particularly in enhancing security measures and improving user-centric designs. It aims to provide a holistic understanding of the current state and future potential of personalized AI-based voice assistants in authentication services, offering valuable insights for researchers and practitioners in the field.

Key Words: Voice Recognition Technologies, Facial Recognition, Multimodal Authentication, Secure PINs, Biometric Authentication.