Low complexity recursive coding of spectrum parameters

A low complexity vector quantization scheme for the recursive coding of speech spectrum parameters is proposed. In this scheme, the joint probability density function (pdf) of the spectrum parameters of successive speech frames is modelled using a Gaussian mixture model whose parameters are estimated using the Expectation Maximization (EM) algorithm. The conditional density of the spectrum parameters of the current speech frame based on the quantized values of the spectrum parameters of previous speech frames is used to generate a new codebook for every current speech frame. An efficient quantization scheme using transform coding and bit allocation techniques which allows easy and computationally efficient mapping from observation to quantized value is developed. Transparent quality speech for the first order fixed rate recursive coding case is achieved at 20 bits per frame.