| EPSRC Reference: |
EP/P017746/1 |
| Title: |
Natural speech Automated Utility for Mental health |
| Principal Investigator: |
Gasic, Dr M |
| Other Investigators: |
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| Researcher Co-Investigators: |
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| Project Partners: |
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| Department: |
Engineering |
| Organisation: |
University of Cambridge |
| Scheme: |
First Grant - Revised 2009 |
| Starts: |
30 April 2017 |
Ends: |
29 July 2018 |
Value (£): |
100,724
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| EPSRC Research Topic Classifications: |
| Artificial Intelligence |
Computational Linguistics |
| Human Communication in ICT |
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| EPSRC Industrial Sector Classifications: |
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| Related Grants: |
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| Panel History: |
| Panel Date | Panel Name | Outcome |
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01 Dec 2016
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EPSRC ICT Prioritisation Panel Dec 2016
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Announced
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Summary on Grant Application Form |
Promotion of mental well-being is at the core of the World Health Organisation's action plan on mental health 2013--2020, with particular emphasis on the prevention of mental illnesses.
Indeed, prevention has long been neglected: if we were to make an analogy with dentistry, the state in mental health is such that we know how to treat caries, but we have yet to discover toothpaste.
Although there is research to suggest that internet-based therapy can be beneficial, there has been little progress on automated mental health advice systems. In the last decade, machine learning has made a huge impact on various areas including spoken dialogue systems.
Still, the application of statistical spoken dialogue systems has so far been limited to simple information-seeking tasks. Here we propose NAUM---Natural speech Automated Utility for Mental health---, a purely data-driven spoken dialogue system that can be used for maintaining mental well-being. Mental health experts will work on developing NAUM's knowledge, its behaviour will be optimised by novel reinforcement learning algorithms and it will support spoken interaction.
This ground breaking research will bring the potential of machine learning in spoken dialogue modelling to an application which has a clear benefit for society. NAUM will provide anonymous support that can be accessed by anyone, any time, anywhere, for free.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.cam.ac.uk |