On losses, pauses, jumps and the wideband E-Model is our attempt to derive human competitive models for speech quality estimation. Speech quality estimation is an important problem in telecommunication networks. Ability to estimate speech quality well allows adequate network transmission planning and monitoring the wellbeing of a VoIP network. In our approach, we employed machine learning techniques to derive models for quality estimation. In particular, we employed genetic programming, a kind of evolutionary computation technique.
We conducted this project right in the heart of where speech quality matters most. To this end, we worked in Orange Labs, Lannion, France on a year long project. You can peruse our whole work as follows:
On Losses, Pauses, Jumps and the Wideband E-Model – IEEE Xplore Document
There is an increasing interest in upgrading the EModel, a parametric tool for speech quality estimation, to the wideband and super-wideband contexts. The
On Losses, Pauses, Jumps and the Wideband E-Model by OptimumT is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License.