Our September 2023 intake ("Cohort 5") was our final cohort of students. We are no longer recruiting students to join the CDT. 

However, the CDT has funds available to support one affiliated, fully-funded 3.5 year PhD studentship in Spoken Language Technologies. As an affiliated student, you will be welcome to participate in CDT activities and events but you will not be a formal member of the CDT and you will undertake the University of Sheffield's standard Doctoral Development Programme (DDP) training programme as opposed to the CDT's PGDip training programme. You will start in September 2026.

Home and International students may apply. Regardless of your fees status (Home or International), all fees will be paid (in addition to a full stipend). International candidates should be aware that the award does not cover funding for costs related to relocation to the UK, such as visa fees or the NHS surcharge. 

This studentship is currently advertised on jobs.ac.uk and FindAPhD.

We are seeking an excellent candidate to work on a specific speech processing project; the project is supervised by Prof Thomas Hain (a world leader in speech recognition and Fellow of the International Speech Communication Association, ISCA). 

Metamodelling of Speech Domains

Speech is a highly variable signal that is often recorded in complex environments and under sub-optimal conditions. The information contained in a recorded speech signal is not limited to  just the words spoken; the signal also includes, for example, information on speaker identity or conversation style. Depending on the task at hand, different aspects of the speech signal are important, leading to different models being used. However, in recent years model topologies for automatic speech recognition and many other speech processing tasks have started to converge - driven by research focus on generalisation. Still, the issue of domain dependence often remains. Recently there has been an increased interest in model combination and model editing, for example through disentanglement of so-called task vectors. 

In this project we aim to explore how different aspects of speech data are expressed in model space, in the context of automatic speech recognition and diarisation. The objective of this work is to explore methods to attribute elements of model spaces to skills, or specific aspects of the data. This can be used either as input in hypermodelling, where new models for specific domains are generated, or for improved structuring in model training and design. 

Work on this project  will require research into novel methods to represent model variations and attribute them to specific attributes and tasks. The value of such models should then be demonstrated by informing training and inference processes. A range of different strategies can be explored, including new ways to derive model distributions and model parameter predictions. Experiments should be conducted on a range of tasks of different complexity in the context of different data domains, for example speech classification, speech recognition, and diarisation.

The studentship offers you the following benefits:

• Fully funded 3.5 year studentship covering Home or International tuition fees and an enhanced stipend at the basic UKRI rate plus £3,500 (totalling £25,305 per year, tax free for 2026/27)*.

• Research and training support grant of £2,500 per annum to cover research expenses and conference attendance. 

• Supervision from world-renowned academics.

• Laptop and dedicated desk in the CDT's student workspace equipped with dual external monitors, keyboard and mouse, and headset.

• Exposure to the cross-disciplinary approaches and co-creation of novel SLT methods and applications.

• A dedicated workspace purely for CDT and affiliated students within a collaborative and inclusive research environment hosted by the School of Computer Science.

• Enrollment on the University of Sheffield's Doctoral Development Programme (DDP) training programme. 

• Work and live in Sheffield – a cultural centre on the edge of the Peak District National Park which is in the top ten most affordable UK university cities (3rd the Unifresher Cheapest Cities In The UK For Students To Live In 2026; 3rd lowest in the UK for average rent in the NatWest Student Living Index 2025).

* Tax and National Insurance: Stipend payments are training awards and not regarded as income for income tax purposes. Earnings received from sources such as teaching and demonstrating may be taxable and should be aggregated with income from any employment when assessing income tax liability in any tax year – this is particularly relevant for the tax year in which the award ends. It is your responsibility to ensure you understand your tax liabilities throughout your award. The University and UKRI are not able to provide advice on tax, national insurance, pensions or on benefits issues.

No additional payments will be made for your National Insurance contributions. You can, if you wish, pay contributions as non-employed persons. You should consult your local office of the Department for Work and Pensions about your position to determine the impact of non-payment of contributions on any future claims for benefit including the basic State Pension. You may become liable for contributions in connection with any paid teaching or demonstrating which you undertake.