Generating localised sound fields to promote conversational privacy

Techniques from spatial audio, noise cancellation and array processing, such as beamforming and sound field control, may be adapted to satisfy this objective perceptually, within a machine learning framework. The work will be realised as a responsive multi-channel sound system and evaluated in terms of its auditory performance, combining audio experiments with computer-based development.

The University of Surrey hosts arguably the widest range of excellent audio and audio-visual research facilities in the UK, including the Surrey Sound Sphere and around 30 associated studio, control room, listening room and lab spaces.

The project benefits from the excellent scientific environment, facilities and resources provided by the Centre for Vision, Speech and Signal Processing (CVSSP) at the University of Surrey and from collaboration with the Foreign, Commonwealth and Development Office (FCDO) and the National Physical Laboratory (NPL). The researchers can also spend time on site at NPL and be part of the wider collaborative network between NPL, University of Surrey and the University of Strathclyde. A generous stipend is offered in addition to funding for tuition fees and research training. 

We are looking for intelligent, capable and well-motivated applicants with MEng / MSc degree in Engineering, Mathematics, Physics or Computer Science.  The scholarship is primarily open to UK nationals; EU, Commonwealth  or USA nationals may also be considered. 

You will need to meet the minimum entry requirements for our Vision, speech and signal processing PHD programme.

Open to UK nationals and those who pay UK/home rate fees. See UKCISA for further information

In addition, you will have to be resident in the UK for at least two, ideally 3 years (at the time of application) to meet the requirement for additional security clearances required to carry out work as part of this project.

Additionally we are looking for a candidate with:

• A First Class undergraduate degree or MSc with Distinction (or equivalent overseas qualification) in mathematics,  computer science, physics or engineering.
• Excellent mathematical, analytic, and programming skills.  
• ​Previous experience in tomographic imaging would be advantageous.