Everything about Line Spectral Pairs totally explained
Line Spectral Pairs (LSP) or
Line Spectral Frequencies (LSF) are used to represent
Linear Prediction Coefficients (LPC) for transmission over a channel. LSPs have several properties (for example smaller sensitivity to quantisation noise) that make them superior to direct quantisation of LPCs. For this reason, LSPs are very useful in
speech coding.
Mathematical foundation
The LP
polynomial
where P(z) corresponds to the vocal tract with the
glottis closed and Q(z) with the
glottis open.
While A(z) has complex roots anywhere within the unit circle (z-transform), P(z) and Q(z) have the very useful property of only having roots
on the unit circle, hence P is a
palindromic polynomial and Q an
antipalindromic polynomial. So to find them we take a test point
and evaluate
and
using a grid of points between 0 and pi. The zeros (roots) of P(z) and Q(z) also happen to be interspersed which is why we swap coefficients as we find roots. So the process of finding the LSP frequencies is basically finding the roots of two polynomials of order p+1. The root of P(z) and Q(z) occur in symmetrical pairs at +/-w, hence the name Line Spectrum Pairs (LSPs). Because all the roots are complex and two roots are found at 0 and
, only p/2 roots need to be found for each polynomial. The output of the LSP search thus has p roots, hence the same number of coefficients as the input LPC filter (not counting
).
To convert back to LPCs, we need to evaluate
by "clocking" an impulse through it N times (order of the filter), yielding the original filter, A(z).
Properties
Line Spectral Pairs have several interesting and useful properties. When the roots of P(z) and Q(z) are interleaved, stability of the filter is ensured if and only if the roots are monotonously increasing. Moreover, the closer two roots are, the more resonant the filter is at the corresponding frequency. Because LSPs are not overly sensitive to quantization noise and stability is easily ensured, LSP are widely used for quantizing LPC filters. At last, LSPs are a good representation for interpolating filters.
Sources
Speex manual
and source code (lsp.c)
Tony Robinson: Speech Analysis
"The Computation of Line Spectral Frequencies Using Chebyshev Polynomials"
/ P. Kabal and R. P. Ramachandran. IEEE Trans. Acoustics, Speech, Signal Processing, vol. 34, no. 6, pp. 1419-1426, Dec. 1986.
Includes an overview in relation to LPC.
"Line Spectral Pairs" chapter
as an online excerpt (pdf) / "Digital Signal Processing - A Computer Science Perspective" (ISBN 0-471-29546-9) Jonathan Stein.Further Information
Get more info on 'Line Spectral Pairs'.
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