Efficient LPC Quantization Methods - Digital Speech: Coding for Low Bit Rate Communication Systems - page 84

5

Efficient LPC Quantization
Methods

5.1 Introduction

Linear predictive coding is a very powerful analysis technique and is used
in many speech processing systems. In speech coding and synthesis systems,
the analysis techniques for obtaining the LP coefficients (LPC), e.g. autocorre-
lation, covariance, lattice, and the quantization of the LPC are very important
aspects of LPC analysis as minimization of coding capacity is the ultimate
aim in these applications. The main objective of the quantization procedure
is to code the LPC with as few bits as possible without introducing audible
spectral distortion. Whilst perfect reconstruction is not possible, subjective
transparency is achievable. Quantization of the LPC is usually performed by
transforming the LPC to other forms which enables predictive coding and
allows an easy filter stability check. The most popular LPC transformation is
the use of Line Spectrum Pairs (LSP), related to the Line Spectral Frequency
(LSF) representation of the LPC [1, 2]. In this chapter, the LSF representation
of the LPC will be described, followed by various LPC quantization schemes
using LSF transformation.

5.2 Alternative Representation of LPC

As was shown in Chapter 4, the LPC filter is given by

1

H(z) = (5.1)

p

α i z − i 1 +

i = 1

where p is the order of LPC filter.