Abstract:Compressed Sensing is a research focus rising in recent years. On the basis of the signal’s sparse representation in the KLT domain, this paper proposes an approximate KLT method using template matching and studies on the corresponding compressed speech signal sensing. First, it verifies the sparsity of speech signal in the approximate KLT domain. Second, by speech signal and a measurement matrix, it arranges measurements of fixed or adaptive length according to frame energy. Third, according to the measurements, it finds the speech signal’s sparsest coefficient vector through L1 optimization algorithm to recover the speech signal. Simulation results demonstrate that compressed speech signal sensing in the approximate KLT using template matching has good performance.