Intelligent Voice-Based Door Access Control System Using Adaptive-Network-based Fuzzy Inference Systems (ANFIS) for Building Security
Abstract
Secure buildings are currently protected from unauthorized access by a variety of devices. Even though there are many kinds of devices to guarantee the system safety such as PIN pads, keys both conventional and electronic, identity cards, cryptographic and dual control procedures, the people voice can also be used. The ability to verify the identity of a speaker by analyzing speech, or speaker verification, is an attractive and relatively unobtrusive means of providing security for admission into an important or secured place. An individual’s voice cannot be stolen, lost, forgotten, guessed, or impersonated with accuracy. Due to these advantages, this paper describes design and prototyping a voice-based door access control system for building security. In the proposed system, the access may be authorized simply by means of an enrolled user speaking into a microphone attached to the system. The proposed system then will decide whether to accept or reject the user’s identity claim or possibly to report insufficient confidence and request additional input before making the decision. Furthermore, intelligent system approach is used to develop authorized person models based on theirs voice. Particularly Adaptive-Network-based Fuzzy Inference Systems is used in the proposed system to identify the authorized and unauthorized people. Experimental result confirms the effectiveness of the proposed intelligent voice-based door access control system based on the false acceptance rate and false rejection rate.
DOI: https://doi.org/10.3844/jcssp.2007.274.280
Copyright: © 2007 Wahyudi, Winda Astuti and Syazilawati Mohamed. This is an open access article distributed under the terms of the
Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
- Access control
- voice
- intelligent
- artificial neural network
- security