The distance measure for line spectrum pairs applied to speech recognition

The Line Spectrum Pair (LSP) based on the principle of linear predictive coding (LPC) plays a very important role in the speech synthesis; it has many interesting properties. Several famous speech compression / decompression algorithms, including the famous code excited linear predictive coding (CELP), are based on the LSP analysis, where the information loss or predicting errors are often very small due to the LSP’s characteristics. Unfortunately till now there is not a satisfying kind of distance measure available for LSP so that this kind of features can be used for speech recognition applications. In this paper, the principle of LSP analysis is studied at first, and then several distance measures for LSP are proposed which can describe very well the difference between two groups of different LSP parameters. Experimental results are also given to show the efficiency of the proposed distance measures.