The independent hypothesis between frames in vocal effect(VE) recognition makes it difficult for frame based spectral features to describe the intrinsic temporal correlation and dynamic change information in speech phenomena. A novel VE detection method based on echo state network(ESN) is proposed. The input sequences are mapped into a fixed-dimensionality vector in high dimensional coding space by reservoir of the ESN. Then, radial basis function(RBF) networks are employed to fit the probability density function(pdf) of each VE mode by using the vectors in the high dimensional coding space. Finally, the minimum error rate Bayesian decision is employed to judge the VE mode. The experiments which are conducted on isolated words test set achieve 79.5% average recognition accuracy, and the results show that the proposed method can overcome the defect of the independent hypothesis between frames effectively.
To solve the efficiency problem of batch anonymous authentication for vehicular Ad-hoc networks （VANET） , an improved scheme is proposed by using bilinear pairing on elliptic curves. The signature is jointly generated by roadside unit （RSU） node and vehicle, thus reducing the burden of VANET certification center and improving the authentication efficiency, and making it more difficult for attacker to extract the key. Furthermore, under random oracle model （ROM） security proof is provided. Analyses show that the proposed scheme can defend against many kinds of security problems, such as anonymity, man-in-the-middle （ MITM ） attack, collusion attack, unforgeability, forward security and backward security etc. , while the computational overheads are significantly reduced and the authentication efficiency is effectively improved. Therefore, the scheme has great theoretical significance and application value under computational capability constrained Internet of things （IoT） environments.
