Quality estimation of synthesized speech transmitted over IP channel using genetic programming approach

In this article, an evolutionary algorithm known as Genetic Programming (GP) was used to design a parametric speech quality estimation model. Nowadays, GP is one of the machine learning techniques employed in a quality estimation process. In principle, the set of quality-affecting parameters was used as an input to the designed estimation model based on GP approach in order to estimate a quality of synthesized speech transmitted over IP channel (VoIP environment). The performance results obtained by the designed estimation model have confirmed the good properties of genetic programming, namely good accuracy and generalization ability; this makes it to be perspective approach to a quality estimation of this type of speech in the corresponding environment. The developed model can be helpful for network operators and service providers implementing it in planning phase or early-development stage of telecommunication services based on synthesized speech.