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Rashid, J., Teh, Y.W., Memon, N.A., Mujtaba, G., Zareei, M., Ishtiaq, U., Akhtar, M.Z. and Ali, I. (2020) Text-Independent Speaker Identification through Feature Fusion and Deep Neural Network. IEEE Access, 8, 32187-32202.
https://doi.org/10.1109/ACCESS.2020.2973541

has been cited by the following article:

• TITLE: Use of AI Voice Authentication Technology Instead of Traditional Keypads in Security Devices

  AUTHORS: Deepak Ramesh Chandran

  KEYWORDS: Artificial Intelligence, Voice Authentication, Blockchain, Data Security, Automatic Speech Recognition, Voice Biometrics

  JOURNAL NAME: Journal of Computer and Communications, Vol.10 No.6, June 13, 2022

  ABSTRACT: Traditional keypads and text-based passwords are vulnerable to scams and hacks, leading to enormous levels of embezzlement and frauds apart from various other threats to data security. AI based voice authentication holds unparalleled value for data protection, security, and privacy, by providing an effective alternative to traditional password-based protection. This paper reports the findings of a limited literature review that forms the basis for further research towards enhancing the reliability and security of AI voice authentication. Based on the findings of the review of existing literature, this paper proposes that integration of the blockchain technology with the AI voice authentication can significantly enhance the data security, starting from mobile devices to the security of big agencies and banks. The key processes in implementing an AI voice authentication system are proposed as a conceptual model, to facilitate further research for implementation.