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Details of Grant 

EPSRC Reference: GR/S85511/01
Title: Statistical models to relate speech gestures to meaning.
Principal Investigator: Jackson, Dr P
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department: Vision Speech and Signal Proc CVSSP
Organisation: University of Surrey
Scheme: First Grant Scheme Pre-FEC
Starts: 01 January 2005 Ends: 31 December 2007 Value (£): 126,849
EPSRC Research Topic Classifications:
Human Communication in ICT
EPSRC Industrial Sector Classifications:
Creative Industries
Related Grants:
Panel History:  
Summary on Grant Application Form
The proposed project aims to model the statistical properties of speech dynamics that correspond to real articulatory gestures, and to incorporate the models into an automatic speech recognition (ASR) system. The human vocal apparatus provides major constraints on the speech sounds that can be produced (particularly on how they can vary over time). These constraints offer the potential of substantial improvements in ASR performance under it: most challenging conditions: for spontaneous speech recognition in noisy environments. In contrast to earlier work using piecewise linear motion, this project focuses on understanding the characteristics of articulatory movements that are important for recognition, and how they might be properly represented in a generic model. The model parameters are to be learnt automatically from appropriate speech training data, using expectation maximisation techniques, in order accurately to describe gestures made by the tongue, jaw, lips, etc. By extending these techniques to learn the parameters of dynamic articulatory models, we intend not only to achieve improvements in recognition accuracy (with rigorous evaluation on unseen test data), but also to obtain a realistic and useful representation of the way fluent speech is produced.
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Organisation Website: http://www.surrey.ac.uk