The UK Research and Innovation (UKRI)
Speech and Language Technologies (SLTs) are a central element of Artificial Intelligence (AI). Located at a world leading research institution in the field, this UKRI AI Centre for Doctoral Training (CDT) will host at least 60 PhD students over a period of 8 years.
Far beyond standard research training, the CDT students will be part of a vibrant research centre that further provides training in engineering skills, leadership, entrepreneurship, and responsibility to society.
AI had been identified in the UK Government’s Industrial Strategy and one of the four Grand Challenges and an area for strategic growth. The CDT will help address this by training students in the theory and application of computational speech and language processing.
The centre is hosted within the Department of Computer Science which has an international reputation for the quality of its research and teaching. In the 2014 Research Excellence Framework (REF – the UK Government’s national assessment of university research), 92% of our research work was rated world leading (4*) or internationally excellent (3*) in terms of its originality, significance and rigour.
EPSRC prosperity outcomes
The Engineering and Physical Sciences Research Council (EPSRC) have identified that the future competitiveness and creativity of the UK economy requires the successful development of world-leading products, processes and technology based on the discovery and innovation in the mathematical and physical sciences, information and computing technologies, and engineering.
The EPSRC aims to anticipate economic and social change, and re-skill the UK workforce with a particular requirement to achieve technical leadership through the development of future scientists, engineers and technologists.
Professor Thomas Hain
Head of the Speech and Hearing Research Group
Prof Hain is a world leader in speech recognition, heads the Voicebase Centre for Speech and Language Technology and is a leader in the speech community.
‘Talking and listening, understanding and expressive communication are skills that we all have. To this day we struggle to build machines that come close to human abilities. To explore and invent methods that allow us to recognise what is spoken, to understand, transform and interpret human communication has been the focus of my research. I am interested in machine learning methods that allow us to model communication and interaction, to be able to help people communicate, learn, and engage with new technology.’
Example of possible topics for supervision include; advanced modelling of speech processes, models of acoustic environments or of language, relationship between languages, and systems that transcribe spoken words, analyse them, transform the signal or the language, and on systems that respond to you and learn from you.
Professor Rob Gaizauskas
Head of the Natural Language Processing Research Group
Prof Gaizauskas is internationally known for his research on information extraction and text mining, temporal information processing, question answering and summarisation.
‘Can we build we build computer programs that “understand” human language? This question is of interest from both a cognitive science/linguistic perspective and from an applied/engineering perspective. What are the syntactic/semantic and pragmatic mechanisms available in human languages and how do intentional agents deploy them to communicate and accomplish goals in the world? How can we use our current, partial understanding of NLP to engineer applications that help people to gain better access to information in massive amounts of textual data and to dynamically interact with intelligent agents via NL dialogue?’
Example of possible topics for supervision include; information extraction/text mining; automatic summarization; semantic annotation of temporal and spatial information; automatic generation of image descriptions; common sense knowledge and NL understanding; task-oriented dialogue.
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