Fast methods for code search in CELP

Abstract

The code excited linear prediction (CELP) technique has the potential for producing high quality synthetic speech at bit rates as low as 4.8 kb/s. Three fast search methods for selecting an optimal excitation sequence from a code book of stochastic vectors are described. The key idea is to inverse-filter the actual speech with the formant and pitch filters to produce a residual error sequence (RES). The residual error is used to identify a neighborhood or a subset of codes for further processing. The first method, called dynamic nearest neighborhood (DNN), attempts to dynamically construct a neighborhood of the K codes of maximum correlation with the residual error. The second method, called nearest fixed neighborhood (NFN), clusters the code book into a fixed number of cells, and code search is performed on the codes of the cell nearest to the RES. The two methods achieve a reduction in the search procedure by a factor of 8-20 times. The third method combines the advantages of the first two methods to attain a reduction from 40 to 50 times. The performance of these techniques and some of their ramifications are addressed