What are Speech and Language Technologies?
Speech and Language Technologies (SLTs) are a range of Artificial Intelligence (AI) approaches which allow computer programs or electronic devices to analyse, produce, modify or respond to spoken and written language. They enable natural interaction between people and computers, translation between all human languages, and analysis of speech and text.
SLTs are underpinned by a number of fundamental research fields including acoustics, signal processing, speech processing, natural language processing (NLP / NLProc), computational linguistics, mathematics, machine learning (ML), physics, psychology, and computer science. If you're interested in any of these topics and are looking to do a PhD, we could be the place for you!
SLTs are established as core scientific/engineering disciplines within AI and have grown into a world-wide multi-billion dollar industry, with massive application potential.
Could we help you?
Would you like to find out more about how SLTs can benefit your company's activities?
For example, would you like to conduct trend analysis from targeted web content? Extract insights from client feedback? Analyse a customer’s speech and adapt the call handler’s engagement in real-time? Deploy chatbots? Or maybe you simply don’t know what’s possible.
Our SLT Consultancy Hub could help!
Our Centre for Doctoral Training
Centres for Doctoral Training (CDTs) bring together diverse areas of expertise to train engineers and scientists with the skills, knowledge and confidence to tackle today’s evolving issues, and future challenges.
They also provide a supportive and exciting environment for students, create new working cultures, build relationships between teams in universities and forge lasting links with industry.
Students are funded for four years and doctoral programmes include technical and transferrable skills training, as well as a research element. We are funded by UKRI, the University of Sheffield as well as industry.
The UKRI Centre for Doctoral Training (CDT) in Speech and Language Technologies (SLT) opened in 2019 and will host more than 50 students over a period of eight years.
The CDT goes far beyond standard research training. Students undertake a unique Doctor of Philosophy (PhD) with Integrated Postgraduate Diploma (PGDip) in SLT Leadership programme.
Students and industry work with a team of over 20 internationally leading SLT researchers, covering all core areas of modern SLT research within the context of a PhD project. These projects are underpinned by a real world application defined by our industry partners.
Our Host School
The CDT is hosted within the School of Computer Science at the University of Sheffield which is itself a world-leading institution in the field of speech and NLP.
The department has an international reputation for the quality of its research as confirmed by its performance in the most recent (2021) Research Excellence Framework audit (REF – the UK Government’s national assessment of university research) in which 99% of our research work was rated world-leading (4*) or internationally excellent (3*) in terms of its originality, significance and rigour. We are rated as 8th nationally for the quality of our research environment, showing that the School of Computer Science is a vibrant and progressive place to undertake research.
The School has arguably the largest mass of Speech and Language Technologies researchers in a single aacdemic unit in the UK and has an outstanding track record in research grant awards, impact and award of PhDs. In addition, they have an extensive set of international industrial collaborators, across many sectors and ranging from SMEs to global players.
Our industrial partners
Ofcom
Apple
Amazon Research
ZOO Digital
Huawei
VoiceBase / LivePerson
Meta (formerly Facebook)
Microsoft Research
WS Audiology
3M
TribePad
Scribetech
Toshiba
Factmata
Ieso Digital Health
ITSLanguage
Recordsure
Tech Nation
Therapy Box
Gweek
Signal A.I.
Textio
NHS Digital
OCLC
Emotech
Nuance
SoapBox Labs
Jam Creative Studios
Netcall
Sheffield Digital
MapR
BTS
Kollïder
Solvay
Ontotext