Title :
Efficient distance measure for quantization of LSF and its Karhunen-Loeve transformed parameters
Author :
Vu, Hai Le ; Lois, László
Author_Institution :
Dev. Div., Siemens Ltd., Budapest, Hungary
fDate :
11/1/2000 12:00:00 AM
Abstract :
This paper presents a new distance measure that is based on the spectral sensitivity of the line spectrum frequency parameters (LSFs) and its Karhunen-Loeve (KL) transformed coefficients. It is shown that the proposed distance measure achieves better performance of vector quantization (VQ) compared to other methods in the field of LSF coding. In most cases, the percentage of outliers is reduced when using the new one, compared to the best results of using other conventional weighting functions, The use of this distance as the weighting function of the LSF transformed parameters is also suggested
Keywords :
Karhunen-Loeve transforms; spectral analysis; speech coding; transform coding; vector quantisation; Karhunen-Loeve transformed parameters; LSF coding; VQ; efficient distance measure; line spectrum frequency parameters; outliers; spectral sensitivity; vector quantization; weighting function; Distortion measurement; Ear; Euclidean distance; Frequency measurement; Humans; Linear predictive coding; Signal synthesis; Speech coding; Speech synthesis; Vector quantization;
Journal_Title :
Speech and Audio Processing, IEEE Transactions on