Month: May 2017

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

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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

Photo by philstephenrichards

NUAV – A Testbed for Development of UAVs

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In a remote town of Pakistan, in an increasing rural setup, we developed a testbed for simulating drone planes. Our idea was that if we could glue a cutting-edge flight simulator with state-of-the-art machine learning algorithms, innovation will follow spontaneously. And it did!

The result of our hard work was that we developed a testbed for developing autonomous unmanned aerial vehicles (UAVs). In doing this our aims were high, our commitments were strict, our passion was profound and our intentions were very civil. Our work has been published in a recent conference. We are sharing useful links for your kind perusal.

NUAV – a testbed for developing autonomous Unmanned Aerial Vehicles – IEEE Xplore Document

Contemporary models of Unmanned Aerial Vehicles (UAVs) are largely developed using simulators. In a typical scheme, a flight simulator is dovetailed with a

Photo by Andrew Turner