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Details of Grant 

EPSRC Reference: EP/P017746/1
Title: Natural speech Automated Utility for Mental health
Principal Investigator: Gasic, Dr M
Other Investigators:
Crawford, Professor MJ
Researcher Co-Investigators:
Project Partners:
Department: Engineering
Organisation: University of Cambridge
Scheme: First Grant - Revised 2009
Starts: 01 February 2017 Ends: 31 January 2018 Value (£): 100,724
EPSRC Research Topic Classifications:
Artificial Intelligence Computational Linguistics
Human Communication in ICT
EPSRC Industrial Sector Classifications:
Healthcare
Related Grants:
Panel History:
Panel DatePanel NameOutcome
01 Dec 2016 EPSRC ICT Prioritisation Panel Dec 2016 Announced
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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Organisation Website: http://www.cam.ac.uk