Design GiggleGate as Desktop Virtual Assistant with Face and Speech Recognition Authentication System

Jasmine Aulia Mumtaz; Kinaya Khairunnisa Komariansyah; Wildan Holik; Reza Pratama; Muhammad Galuh Gumelar; Endang Purnama Giri; Gema Parasti Mindara

doi:10.62951/ijcts.v1i4.113

Authors

Jasmine Aulia Mumtaz IPB University
Kinaya Khairunnisa Komariansyah IPB University
Wildan Holik IPB University
Reza Pratama IPB University
Muhammad Galuh Gumelar IPB University
Endang Purnama Giri IPB University
Gema Parasti Mindara IPB University

DOI:

https://doi.org/10.62951/ijcts.v1i4.113

Keywords:

authentication, face recognition, speech recognition, virtual assistant, security

Abstract

In recent years, virtual assistants have become an integral part of everyday life, simplifying routine tasks and allowing users to focus on more important matters. This research aiming to design GiggleGate, a virtual desktop assistant integrated with both face and speech recognition technology to enhance authentication security. The objective is to develop an authentication system that not only verifies user identity but also provides a more intuitive experience and seamless interaction. The research employs a development methodology to create and implement the system, which integrates face recognition via OpenCV and speech recognition via a Python library. The findings indicate that the integration of these technologies enhances security and user experience by offering dual-factor authentication. The system is expected to contribute to more secure and accessible virtual assistant applications, offering both a practical and efficient solution for users. The implications of this study suggest that the combination of face and speech recognition can provide an effective means to protect user privacy and improve the overall functionality of desktop assistants.

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