Abstract
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.
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