Forward adaptive dual-mode quantizer based on the first-degree spline approximation and embedded G.711 codec

Zoran Peric, Jelena Nikolic, Bojan Denic, Vladimir Despotovic

Research output: Contribution to journalArticleResearchpeer-review

3 Citations (Scopus)


In this paper, we propose a novel model of dualmode quantizer that combines the restricted and unrestricted forward adaptive piecewise linear scalar quantizers based on the first degree-spline functions, one of them being forward adaptive G.711 quantizer used as the unrestricted one. The analysis presented in the paper can be considered as our further research in the field of dualmode quantization. In particular, in our novel model we utilize G.711 codec due to the compatibility reasons and we develop one completely novel model of restricted quantizer based on the first-degree spline approximation, which is optimized for the assumed Laplacian source so that to provide a minimal mean-squared error distortion. Moreover, unlike previous dual-model quantizer models that processed signals in frame-by-frame manner, our novel model utilizes frame/subframe processing of the signal in order to decrease the total bit rate. The theoretical analysis in a wide dynamic range of input signal variances reveals that the proposed model of quantizer is superior versus the unrestricted G.711 quantizer as well as other similar baselines having the same number of quantization levels. In addition, the results of the experimental analysis performed on the real speech signal show a good agreement with the theoretical ones.

Original languageEnglish
Pages (from-to)729-739
Number of pages11
Issue number4
Publication statusPublished - 1 Dec 2019
Externally publishedYes


  • Dualmode quantization
  • Laplacian source
  • Restricted quantization
  • SQNR
  • Scalar quantization


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