Classified vector excitation speech coding

TLDR: A classified vector excitation coding (CVXC) scheme based on selective modelling of the LPC residual which attempts to overcome both these drawbacks by using separate codebooks for separate excitation types.

Abstract: Code excited linear prediction (CELP) has been shown [1] to be capable of achieving high quality speech compression at very low bit rates. However, the original method suffers from the two drawbacks that it requires a large amount of computation, and the Gaussian codebook used is not able to reproduce a sharp impulse in the coded residual waveform. The authors present a classified vector excitation coding (CVXC) scheme based on selective modelling of the LPC residual which attempts to overcome both these drawbacks by using separate codebooks for separate excitation types. A further feature of our coder which helps preserve the nature of pulsive residuals, is the use of pairwise nearest neighbour (PNN) matching [2] to generate the excitation codebooks.