Statistical properties of an LPC distance measure

Several distance measures have been proposed for comparing sets of LPC coefficients. The most popular one has been the "log likelihood ratio" proposed by Itakura [1]. In this paper we discuss this measure (strictly speaking, a somewhat generalized version of it) from both a theoretical and...

Full description

Saved in:
Bibliographic Details
Published inIEEE transactions on acoustics, speech, and signal processing Vol. 27; no. 5; pp. 550 - 558
Main Authors Tribolet, J., Rabiner, L., Sondhi, M.
Format Journal Article
LanguageEnglish
Published IEEE 01.10.1979
Subjects
Additive noise
Linear predictive coding
Linear systems
Noise measurement
Predictive models
Speech enhancement
Speech processing
Statistical analysis
Statistical distributions
White noise
Online AccessGet full text

Cover

More Information
Summary:Several distance measures have been proposed for comparing sets of LPC coefficients. The most popular one has been the "log likelihood ratio" proposed by Itakura [1]. In this paper we discuss this measure (strictly speaking, a somewhat generalized version of it) from both a theoretical and a practical point of view. We derive its statistical properties both when the reference vector is known and when it is estimated from the data. We also show how these properties are affected by windowing, additive noise, and preemphasis. We present results of extensive simulations in support of the theoretical predictions. Finally, we argue that de Souza's [2] recent criticism of this measure is unjustified.
ISSN:0096-3518
DOI:10.1109/TASSP.1979.1163288