Abstract
A study of combining two ways of reducing the redundancy in the digital representation of speech signals is presented. Differential pulse-code modulation (DPCM) encodes the signal into digital form and reduces the redundancy due to correlation in adjacent sample values of the signal. Following this DPCM operation, entropy coding is used to reduce redundancy due to the unequal probabilities of the DPCM quantizer levels to be transmitted. Theoretical studies agree with Computer simalation results with real speech signals. The concepts of sliding entropy and sliding signal to quantizing noise (S/N) ratio are developed to measure the way in which the entropy and S/N ratio vary with time during a speech utterance. Plots of these quantities versus time for four different utterances are shown. Both adaptive and nonadaptive quantizers are studied. And both uniform and minimum mean-square error quantizing rules are included. Buffer length requirements are calculated for the entropy coders.
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