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The authors consider the problem of automated Voice Activity Detection (VAD), in the presence of noise. To attain this objective, they introduce a Sequential Detection of Change Test (SDCT), designed at the independent mixture of Laplacian and Gaussian distributions. They analyze and numerically evaluate the proposed test for various noisy environments. In addition, they address the problem of effectively recognizing the possible presence of cyber exploits in the voice transmission channel. They then introduce another sequential test, designed to detect rapidly and accurately the presence of such exploits, named Cyber Attacks Sequential Detection of Change Test (CA-SDCT).
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