Spectral coding of speech LSF parameters using Karhunen-Loeve transform

In this paper, the use of optimal Karhunen-Loeve (KL) transform for quantiz ation of speech Line spectrum frequency (LSF) coefficients is studied. Both scalar quantizer (SQ) and vector quantizer (VQ) schemes are developed to e ncode efficiently the transform parameters after operating one or two-dimen sional KL transform. Furthermore, the SQ schemes are also combined with ent ropy coding by using Huffman variable length coding (VLC). The basic idea i n developing these schemes is utilizing the strong correlation of LSF param eters to reduce the bit rate for a given level of fidelity. Since the use o f global statistics for generating the coding scheme may not be appropriate , we propose several adaptive KL transform systems (AKL) to encode the LSF parameters. The performance of all systems for different bit rates is inves tigated and adequate comparisons are made. It is shown that the proposed KL transform coding systems introduce as good as or better performance for bo th SQ and VQ in the examined bit rates compared to other methods in the fie ld of LSF coding.