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[AUDITORY] 2 salaried PhD positions at the University of Sheffield - speech tech for pathological speech



Applications are invited for two three-year Early Stage Researcher PhD positions in the processing and development of speech technology for pathological speech.

Salary:  £25,826 per annum plus a  £5,650 per annum Mobility Allowance (available to all post holders) and a £2,354 per annum non-pensionable Family Allowance (available to those in a legally recognised partnership.)

The positions are part of the new H2020 Marie-Curie Network TAPAS (www.tapas-etn-eu.org). TAPAS brings together a network of Universities, clinical partners and industrial partners to address the communication problems faced by the increasing number of people across Europe living with debilitating speech pathologies (e.g., due to stroke, Alzheimer’s, Parkinson's, etc).

http://www.jobs.ac.uk/job/BJF701/marie-curie-early-stage-researcher-tapas/

Eligibility Criteria:

Early Stage Researchers (ESRs) shall, at the time of recruitment by the host organization, be in the first four years (full-time equivalent research experience) of their research careers.

- The ESR may be a national of a Member State, of an Associated Country or of any Third Country. 
- The ESR must not have resided or carried out her/his main activity (work, studies, etc.) in the country of her/his host organization for more than 12 months in the 3 years immediately prior to her/his recruitment.
- Holds a Master’s degree or equivalent, which formally entitles to embark on a Doctorate.
- Does not hold a PhD degree.

Duration of recruitment: 36 months.

To Apply: http://www.jobs.ac.uk/job/BJF701/marie-curie-early-stage-researcher-tapas/   

(Closing Date: May 17th)

The two projects available at the University of Sheffield are:

(i) Phrase-based speech recognition for people with moderate to severe dysarthria.

The objective is to explore methods for handling larger-vocabulary, phrase-based speech recognition of dysarthric speech including different input strategies, better acoustic modelling, better data capture approaches and better machine learning for an inherently sparse data domain. In particular we will be looking at articulatory representation and deep learning techniques for acoustic to articulatory inversion.

(ii) Using Speech Analysis to Detect Onset and Monitor Cognitive Decline.

The objective is to develop speech technology that can detect, as early as possible, the onset of cognitive decline which might lead to dementia. This must be done in an unobtrusive manner. If a decline in cognitive ability is detected the solution will then monitor the progression and predict future cognitive ability. This project will contribute to the state-of-the-art by investigating ways of monitoring and tracking signs of cognitive decline that work on incidental speech as it occurs in people’s homes. This differs from most current research approaches that tend to focus on planned recordings such as timed naming or picture description tasks.

The work in both projects will focus on statistical and machine learning techniques to address the problems, but it will also involve aspects of human understanding, based on a strong interaction with academic, clinical and end-user partners in the TAPAS network. The research will be conducted as part of the Speech and Hearing research group in Sheffield, with opportunities for collaborative work with several of the leading universities and industrial partners in TAPAS, and with the expectation of a 3+ month secondments to 2-3 partners in this project based on their topic of research. Further information about the research group can be found at spandh.dcs.shef.ac.uk


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Professor Jon Barker,
Department of Computer Science,
University of Sheffield
+44 (0) 114 222 1824