A fast VSELP speech coder based on mutually orthonormal regular pulse vectors

A new vector sum excited linear prediction (VSELP) speech coder employing mutually orthonormal regular pulse vectors is presented. Since the algorithm uses an efficient vector-sum codebook consisting of mutually orthonormal regular pulse basis vectors, computational load for codebook search can be significantly reduced, while the reconstructed speech quality is equivalent to that of the conventional VSELP. The method, referred to as regular pulse VSELP (RP-VSELP), employs the Gram-Schmidt (GS) procedure to orthonormalize the basis vectors designed in a form of regular pulses. To enhance the SNR performance, the basis vectors are optimized using an iterative closed-loop training process