Efficient quantization of LSF parameters using classified SVQ combined with conditional splitting

In this paper, we propose a classified SVQ of line spectral frequency (LSF) parameters combined with conditional splitting. The proposed algorithm adopts an independent conditional splitting scheme instead of the conventional fixed splitting scheme for each class. Considering the perceptual and spectral sensitivity characteristics of LSF's, we define an LSF perceptual importance index (LPII) to represent the relative perceptual importance of each one. Experimental results have shown that the proposed algorithm, conditional split VQ (CONSVQ), can achieve reduction of 37.5% in searching complexity while maintaining the performance of quantization. From these results, we have found that the performance of VQ can be enhanced by considering and using the difference in relative importance of LSF's.