Efficient procedures for finding the optimum innovation in stochastic coders

Stochastic linear predictive coders have the potential for producing high quality synthetic speech at bit rates as low as 4.8 kbits/sec. However, these coders are computationally very complex requiring more than 500 million multiply-add operations per second - a capability much beyond the reach of present digital hardware. Most of the complexity in stochastic coders comes from the search procedure used to determine the optimum innovation sequence from a random code book of white Gaussian sequences. This paper will describe several procedures to simplify the search in stochastic coders. The computational efficiency is achieved by moving the search from time domain to another domain where the convolution (filtering) operation in the search procedure is reduced to a single multiplication operation. The new procedures have reduced the computational load by a factor of approximately 20 without producing any additional degradation in synthetic speech.