On Losses, Pauses, Jumps and the Wideband E-Model

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@Article{Raja:IEEEAccess,
  author =       "Muhammad Adil Raja and Anna Jagodzinska and 
                 Vincent Barriac",
  title =        "On Losses, Pauses, Jumps and the Wideband E-Model",
  journal =      "IEEE Access",
  note =         "accepted for publication",
  keywords =     "genetic algorithms, genetic programming, Loss, Pause,
                 Jump, GP, WB-PESQ",
  ISSN =         "2169-3536",
  DOI =          "doi:10.1109/ACCESS.2017.2705428",
  size =         "19 pages",
  abstract =     "There is an increasing interest in upgrading the
                 EModel, a parametric tool for speech quality
                 estimation, to the wideband and super-wideband
                 contexts. The main motivation behind this has been to
                 quantify the quality gain lent by various new codecs
                 and communication situations. There have been numerous
                 such contributions, and all of them have been more or
                 less successful. This paper reports on an extension of
                 the E-Model to the mixed narrowband/wideband (NB/WB)
                 context. More specifically, we take a novel approach
                 towards deriving effective equipment impairment factors
                 (Ie;WB;eff ) by taking into account additional
                 impairments related to the underlying communications
                 network. These additional impairments are the pause and
                 jump temporal discontinuities along with
                 network-related loss and pure codec-related
                 impairments. While the effect of loss is a thoroughly
                 studied topic and has been integrated into to the
                 E-Model, pauses and jumps have been given little
                 attention. Pauses and jumps manifest themselves as
                 temporal dilation and contraction, respectively, in the
                 resulting speech signal that is presented to the
                 listener and are normally caused by jitter and jitter
                 buffer interaction. In this work, we initially present
                 a 4-state Markov model to characterize, and also
                 emulate, loss, pause, and jump impairments. Then we
                 present alternate models for computing effective
                 equipment impairment models. A large number of test
                 stimuli were generated using different NB and WB
                 codecs. WBPESQ was used to evaluate the stimuli.
                 Genetic programming (GP) was employed to derive
                 equipment impairment factors. The proposed models have
                 a high correlation with WB-PESQ. We claim that the
                 models proposed by us outperform the existing E-Model
                 by a factor of approximately 29percent while using
                 WBPESQ as a reference model. The models also outperform
                 the EModel against results from auditory tests. It is
                 also shown that the models outperform the results of
                 multiple linear regression.",
  notes =        "Also known as \cite{7934120}",
}

Genetic Programming entries for Adil Raja Anna Jagodzinska Vincent Barriac

Citations