학술논문

Edge-Driven Biometrics and Facial Recognition for Virtual Assistant
Document Type
Conference
Source
2023 International Conference on Energy, Materials and Communication Engineering (ICEMCE) Energy, Materials and Communication Engineering (ICEMCE), 2023 International Conference on. :1-7 Dec, 2023
Subject
Communication, Networking and Broadcast Technologies
Engineered Materials, Dielectrics and Plasmas
Power, Energy and Industry Applications
Face recognition
Authentication
Personal voice assistants
Software
Task analysis
Usability
Testing
Multifactor Authentication
Face Recognition
Virtual Assistant
Voice Identification
KNN Classifier
Haar Cascade
Gaussian Mixture Model (GMM)
Language
Abstract
In modern society, time is essential. Recent advances in technology have accelerated the emergence of assistance systems for individuals in their everyday lives. Quick and correct information at the right time needs computerization. In the existing voice assistants, the proper authentication of the user for security purposes is not precise. Inculcating the face and voice biometrics will add up security for the system. To ensure each user’s data and personal information is properly maintained, we provide Multifactor authentication. Also, a lot of time is spent on tedious repetitive tasks which can be reduced by using a virtual assistant. This paper presents a combination of different technologies like Edge driven biometrics, Computer vision, and Machine Learning. The model was designed and developed for both personal mode and general mode. Usability testing was carried out for several use scenarios in order to assess performance.