engleski

Switched-adaptive interframe vector prediction with binary-tree searched predictors

An approach for reduction of complexity of the switched adaptive interframe vector prediction used for coding of the speech spectrum envelope is proposed in this paper. To facilitate the search through the set of switched predictors used for prediction of the input LSF (Line Spectral Frequencies) vector, the predictors are organized in a binary-tree structure. For the conventional full-searched SIVP coder with N=2b predictors, prediction must be performed for all of them to determine the best one, while only 2b predictions are sufficient for the proposed binary-tree searched coder. A design procedure for obtaining optimal binary-tree structured predictors is given. The effectiveness of the proposed coder is evaluated and results are compared to the baseline full-searched coders as a function of the number of predictors, and resolution of vector quantizers used for quantization of the prediction residual. Discussion of possible applications of the proposed coder is also given.

interframe coding; line spectrum frequencies (LSF); vector linear prediction; binary search

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