Analytical Model for Estimating the Bounds in Predictive Entropy Coding of Digital Speech Signals

A detailed analysis of estimating the upper bounds in predictive entropy coding of digital speech signal is carried out in this paper. Lossless speech compression is exploited to measure the useful information content of the data. The bit rate achieved by the reversible compression takes into accoun...

Full description

Saved in:
Bibliographic Details
Published in:Wireless personal communications 2015-05, Vol.82 (2), p.675-687
Main Author: Samcovic, Andreja
Format: Article
Language:English
Subjects:
Coding
Communications Engineering
Computer Communication Networks
Digital
Engineering
Entropy
Estimating
Gain
Mathematical models
Networks
Noise
Signal,Image and Speech Processing
Speech
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:A detailed analysis of estimating the upper bounds in predictive entropy coding of digital speech signal is carried out in this paper. Lossless speech compression is exploited to measure the useful information content of the data. The bit rate achieved by the reversible compression takes into account both the contribution of the observation noise i.e. information regarding to statistical uncertainty, which is not relevant to the user, and the intrinsic information of hypothetically noise-free speech. An entropy model of the speech source is defined in order to estimate the upper bound on SQNR gain in entropy coding of digital speech signals. The gain is calculated for speech predictive coding system with non-adaptive quantizer for white and correlated noise, respectively.
ISSN:0929-6212
1572-834X
DOI:10.1007/s11277-014-2193-1