Environmental Interference Cancellation of Speech with the Radial Basis Function Networks: An Experimental Comparison

In this paper, we use Radial Basis Function Networks (RBFN) for solving the problem of environmental interference cancellation of speech signal. We show that the Second Order ThinPlate Spline (SOTPS) kernel cancels the interferences effectively. For make comparison, we test our experiments on two conventional most used RBFN kernels: the Gaussian and First order TPS (FOTPS) basis functions. The speech signals used here were taken from the OGI Multi-Language Telephone Speech Corpus database and were corrupted with six type of environmental noise from NOISEX-92 database. Experimental results show that the SOTPS kernel can considerably outperform the Gaussian and FOTPS functions on speech interference cancellation problem. Keywords—Environmental interference, interference cancellation of speech, Radial Basis Function networks, Gaussian and TPS kernels.