Novel parameter-based models estimating quality of synthesized speech transmitted over IP network based on Genetic Programming approach

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Mrvova:2013:RADIOELEKTRONIKA,
  author =       "Miroslava Mrvova and Peter Pocta",
  booktitle =    "23rd International Conference Radioelektronika, 2013",
  title =        "Novel parameter-based models estimating quality of
                 synthesized speech transmitted over IP network based on
                 Genetic Programming approach",
  year =         "2013",
  month =        "16-17 " # apr,
  pages =        "361--366",
  address =      "Pardubice, Czech Republic",
  keywords =     "genetic algorithms, genetic programming, speech
                 quality estimation, synthesised speech, packet loss,
                 speech codec",
  DOI =          "doi:10.1109/RadioElek.2013.6530946",
  abstract =     "In this paper, Genetic Programming (GP) based on
                 symbolic regression approach [1] was used to design
                 parameter-based speech quality estimation models. In
                 particular, the models have been designed to estimate a
                 quality of synthesised speech transmitted over IP
                 channel. In principle, the idea is to apply an
                 appropriate set of quality-affecting parameters (e.g.
                 parameters characterising packet loss process, speech
                 codec type, type of synthesised speech) as an input of
                 the designed estimation models. Those quality-affecting
                 parameters together with the corresponding speech
                 quality values predicted by PESQ (Perceptual Evaluation
                 of Speech Quality) [2] are used in training process of
                 the designed models in order to define a relationship
                 between the used quality-affecting parameters and the
                 corresponding speech quality values. Regarding the
                 usage of PESQ as a source of speech quality values, the
                 experiments presented in [3] have shown that PESQ is
                 able to provide accurate predictions of quality of
                 synthesised speech impaired by the impairments used in
                 this study. This study has shown that all designed
                 models provide accurate estimations of quality of
                 synthesised speech transmitted over IP network. An
                 accuracy of the estimations was quantified in terms of
                 the Pearson correlation coefficient R, the respective
                 root mean square error (rmse) and epsilon-insensitive
                 root mean square error (rmse*). The developed models
                 can be useful for network operators and service
                 providers in planning phase or early-development stage
                 of telecommunication services based on synthesised
                 speech.",
  notes =        "Also known as \cite{6530946}",
}

Genetic Programming entries for Miroslava Mrvova Peter Pocta

Citations