Two Fully-funded PhD Studentships in Spoken Language Technologies

Speech and Language Technologies (SLTs) are a range of Artificial Intelligence (AI) approaches for analysing, producing, modifying or responding to spoken and written language. SLTs are underpinned by a number of fundamental research fields including acoustics, signal processing, speech processing, natural language processing, computational linguistics, mathematics, machine learning, physics, psychology, and computer science.

We are seeking two candidates to each work on a specific project in SLT research. These projects specifically target interdisciplinary research, covering both fields of speech and language research; as such, they are jointly supervised by Prof Thomas Hain (a world leader in speech recognition and Fellow of the International Speech Communication Association, ISCA) and Prof Rob Gaizauskas (internationally known for his research on information extraction and text mining, temporal information processing, question answering and summarisation). Candidates will work on one of the following topics:

• Accessible Democracy: UK Houses of Parliament and cross-party Select Committees are at the core of UK democracy. Making the proceedings of these bodies accessible to citizens and journalists is key to holding politicians accountable. This research aims to develop technologies to provide access to the rich linguistic and paralinguistic information in parliamentary audio recordings. Helping journalists to identify newsworthy events is one of the example objectives, alongside more standard tasks such as search, creating alerts or summarisation.
• Analytics of conversations: Spoken conversations are complex and difficult to understand for AI systems. While the words spoken are of obvious importance, paralinguistic information often plays an essential role for a satisfactory and efficient exchange. In practice only goal oriented metrics are used to assess the quality of an exchange, which are not helpful to describe a wide range of conversations such as interviews, story telling or even examinations. Modelling of the participants’ knowledge and state as well as paralinguistic signalling and perception should be used to research novel methods to interpret and understand conversations.
• Evolving communication in embodied agents: Spoken and written language have developed in the course of human evolution and can be viewed as key species-wide adaptations that have enabled us to better survive on our planet. Modelling the development of language in artificial agents with sensory apparatus that are embedded in a physical environment is an exciting research methodology that promises both deeper understanding of human languages and their origins, as well as insights into how to build more effective autonomous agents. This research will build on the state of the art in this area.

About the School/Research Groups

You will be a member of the vibrant Speech and Hearing and Natural Language Processing research groups in the School of Computer Science at the University of Sheffield and an affiliated member of the UKRI AI Centre for Doctoral Training (CDT) in Speech and Language Technologies (SLT) and their Applications. In the School of Computer Science, 99% of our research was rated in the highest two categories in the REF 2021, meaning it was classed as world-leading or internationally excellent. We were also ranked 8th nationally for the quality of our research environment. The University of Sheffield is ranked the number one university in the Russell Group in the National Student Survey 2024 (based on aggregate responses).

The studentship will offer 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 £1,500 (totalling £22,280 tax free for 2025/26).
• Research and training support grant of £2,500 per annum to cover research expenses and conference attendance.
• 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.
• Laptop and dedicated desk in the CDT workspace equipped with external monitors, headset, keyboard and mouse.
• Affiliated membership of the UKRI AI Centre for Doctoral Training (CDT) in Speech and Language Technologies (SLT) and their Applications
• Dedicated workspace for CDT 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) postgraduate researcher training programme.
• Work and live in Sheffield - a cultural centre on the edge of the Peak District National Park which is one of the most affordable UK university cities (4th in the Unifresher Cheapest Cities In The UK For Students To Live In 2024; 6th in the NatWest Student Living Index 2024).

About you

• Self-motivated and enthusiastic about doing research in speech and natural language processing and a commitment to undertaking high quality research.
• High-quality undergraduate (ideally first class) or masters (ideally distinction) degree in computer science, linguistics, statistics, engineering, or a related field.
• Strong maths and programming skills.
• Excellent oral and written communication skills.
• Strong problem-solving abilities.
• If English is not your first language, you must have an overall IELTS grade of 6.5 with a minimum of 6.0 in each component. Equivalent scores in other English language qualifications are welcome; see the University’s guidance for more information on permitted qualifications.

Applying

Applications should be submitted by 23:59 on 13^th April 2025. Shortlisted candidates will be invited to interview. Interviews will be held in Sheffield or via videoconference in mid- to late- May. Should either position remain unfilled at this stage, we will operate a rolling first-come-first-served process of application review and, where applicable, interview.

See our website for full details and guidance on how to apply: slt-cdt.sheffield.ac.uk/apply

For an informal discussion about your application please contact us at: sltcdt-enquiries@sheffield.ac.uk

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