Information theoretic learning for sound analysis

The aim of this PhD project is to investigate information theoretic methods for analysis of sounds.

Start date
1 October 2021
Duration
3 years
Funding information

A stipend of £15,609  for 21/22, which will increase each year in line with the UK Research and Innovation (UKRI) rate, plus Home/EU-rate fee allowance of £4,500 (with automatic increase to UKRI rate each year). The studentship is offered for 3 years.

About

The aim of this PhD project is to investigate information theoretic methods for analysis of sounds. The Information Bottleneck (IB) method has emerged as an interesting approach to investigate learning in deep learning networks and autoencoders. As well as traditional Shannon entropy, the Information Bottleneck method also applies to Renyi and other entropies. Fast and accurate estimation of information is still an active area of research. This project will investigate information-theoretic approaches to analyse sound sequences, both for supervised learning methods such convolutive and recurrent networks, and unsupervised methods such as variational autoencoders. The project will also investigate direct information loss estimators, and new information-theoretic processing structures for sound processing, for example involving both feed-forward and feedback connections inspired by transfer information in biological neural networks.

The project will be supervised by Prof Mark Plumbley, as part of the EPSRC Fellowship on AI for Sound.

We acknowledge, understand and embrace diversity.

Related links
Centre for Vision, Speech and Signal Processing (CVSSP) Fellowship to advance sound to new frontiers using AI

Eligibility criteria

All applicants should have (or expect to obtain) a first-class degree in a numerate discipline (mathematics, science or engineering) or MSc with Distinction (or 70% average) and a strong interest in pursuing research in this field. Additional experience which is relevant to the area of research is also advantageous.

This studentship is open to UK students only. 

IELTS requirements: IELTS 6.5 or above (or equivalent) with no sub-test of less than 6.

How to apply

For enquiries contact Nan Bennett indicating your areas of interest and including your CV with qualification details (copies of transcripts and certificates).

Shortlisted applicants will be contacted directly to arrange a suitable time for an interview.

For further information about our research portfolio and how to apply visit the Centre for Vision, Speech and Signal Processing (CVSSP) research page. 

Vision, Speech and Signal Processing PhD

Contact details

Mark Plumbley
03 BB 01
Telephone: +44 (0)1483 689843
E-mail: m.plumbley@surrey.ac.uk

About CVSSP

CVSSP is a leading UK research centre in audio-visual signal processing, computer vision and machine learning ranked 1st in the UK and 3rd in Europe for Computer Vision. Our Centre is one of the largest in Europe with over 170 researchers and a grant portfolio in excess of £27 million, bringing together a unique combination of cutting-edge sound and vision expertise. Our aim is to advance the state of the art in multimedia signal processing and computer vision, with a focus on image, video and audio applications. Our Centre has a robust track-record of innovative research leading to technology transfer and exploitation in biometrics, creative industries (film, TV, games, VR), communication, healthcare, robotics and consumer electronics.

CVSSP is a destination of choice for postgraduate talent and it is part of the Department of Electrical and Electronic Engineering which is ranked second in the Guardian newspaper league table 2020.  The University of Surrey has recently been ranked 7th in the UK in the 2020 Advance HE Postgraduate Research Experience Survey (PRES).

This PhD project is associated with an EPSRC Fellowship in AI for Sound awarded to Prof Mark Plumbley.

We acknowledge, understand and embrace diversity.

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