The distance measure has a great importance in the phase of the construction of a vector quantizer for LSP parameters as well as in the coding phase. Due to its complexity, the meaningful spectral distance is seldom used for the purpose of quantization. The weighted squared Euclidean distances are mathematicallv more tractahle and are commonly used. Significant differences can be found in the performanance of different distances. The aim of this paper is to study different distance measures used in the field of LSP Coding. A new weighted Euclidean distance will he proposed that not only replaces the spectral distance hut estimates well its exact value. However, the use of squared distances will he justified as well. In a real time application. often weights can not be calculated according to the input vector computation must be done according to the code- words, before coding. This causes some problems in case of split vector quantization or multi stage vector quantization. Some solutions will he given at the end of this paper.