| | Research Associate/Research Fellow - Natural Speech Technology
Fixed-term for 3 years
Salary:
Research Associate - Grade 7: £28,251 to £35,788 per annum
Research Fellow - Grade 8: £36,862 to £44,016 per annum
Closing Date
6 December 2011
The Speech and Hearing research group in the Department of Computer Science (SPandH) is a
partner in the EPSRC Programme Grant in Natural Speech Technology (NST), in collaboration
with the Universities of Edinburgh and Cambridge. NST is a large and ambitious project,
aiming to significantly advance the state-of-the-art in speech technology by making it
more natural, approaching human levels of reliability, adaptability and conversational
richness. The total duration of the NST programme is 5 years and it is organised in
themes that cover a diverse set of collaborative studies in speech recognition and
synthesis. Applications, practical demonstrations and interaction with technology users
in industry are also part of the programme. The successful applicant will work on speech
recognition research topics under the NST programme at Sheffield.
SPandH has developed state-of-the-art automatic speech recognition systems that have
repeatedly shown best performance in international competitions (U.S. NIST) and are
publicly available (www.webasr.org). In clinical applications, SPandH has introduced a
user-driven methodology for personalised speech technology. Together, these advances
form the foundation for Sheffield work within NST. Excellent computing resources are
available to allow ambitious experiments with innovative ideas. This is an opportunity
to work in a well-connected international team with world-leading reputations in speech
recognition research and in collaboration with outstanding groups at the Centre for
Speech Technology Research at Edinburgh and the Machine Intelligence Lab at Cambridge
University.
Applicants should have a PhD (or have equivalent experience) in a related subject area.
Applicants are required to have a good track record in research of speech recognition
and/or machine learning topics. Experience in one or more of the following areas will be
an advantage:
statistical machine learning ,
pattern processing
signal processing
acoustic or language modelling for automatic speech recognition
Solid knowledge of Unix type operating systems and programming in C/C++ is required. For
an appointment at Research Fellow level, experience in research management is essential
as candidates are expected to take a leading role in site scientific management.
For further information see
http://www.jobs.ac.uk/job/ADM425/research-associate-research-fellow
For informal enquiries please contact Thomas Hain (t.hain@dcs.shef.ac.uk) or Phil Green
(p.green@dcs.shef.ac.uk).
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