An Improved Higher-Order Cyclic Cumulant Based VAD Algorithm
一种基于高阶循环累积量的改进型VAD算法

On the basis of cyclostationary feature of speech in short segment, an improved Voice Activity Detection (VAD) algorithm based on higher-order cyclic cumulant is proposed in this paper, which can be applied in complex noise background. In this algorithm, modeling speech signal under MA(Moving Average)model is adopted and estimating cyclic frequency by AMDF(Average Magnitude Difference Function) is chosen to decrease computing complexity as well. Extensive testing on VoIP platform reveals that the algorithm owns good adaptive classification capability in steady noise, such as Gauss (whited and colored) noise, while with a little loss in speech quality, even when it is applied in asymmetric noise conditions.