Speaker recognition using kernel mutual subspace method

We propose a method of person authentication based on lip movement by using the kernel mutual subspace method. Algorithms for person authentication using lip movements have already been developed, but in case that the distribution of lip images has a nonlinear structure, the identification accuracy is degraded because the conventional recognition methods do not assume such nonlinearity. We have investigated the distributions of lip images in feature space and experimentally obtained their nonlinear properties. To solve the problem of nonlinearity, we propose a labiate person authentication method based on the kernel mutual subspace method. We evaluated accuracy and stability of the proposed method with demonstration experiments results.