A new distortion measure for spectral quantization based on the LSF intermodel interlacing property

Abstract

The line spectral frequencies (LSFs) extracted from successive analysis orders are interlaced with each other. This intermodel interlacing property gives a new relationship between the closeness of LSFs and their spectral sensitivities, which motivates a new weighting function for LSF distortion measurement. By applying this new weighting function to LSF quantization, we have achieved a significantly better performance than the conventional heuristic weighting functions in both clean and noise environments. In addition, the proposed weighting function gives better performance than the weighting function based on a high-rate approximation (Gardner weighting (GW)) [W.R. Gardner, B.D. Rao, IEEE Trans. Speech Audio Processing 3 (5) (1995) 367] in noise environments while their performances are comparable in clean environments. Moreover, the complexity of the proposed weighting function is much lower than that of the GW function.