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EPSRC Reference: GR/M75204/01
Title: ROPA: CONTINUOUS-STATE DYNAMICAL SYSTEM MODELS FOR SPEECH RECOGNITION
Principal Investigator: King, Professor S
Other Investigators:
Researcher Co-Investigators:
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Department: Centre for Speech Technology Research
Organisation: University of Edinburgh
Scheme: ROPA
Starts: 01 October 1999 Ends: 31 January 2002 Value (£): 71,143
EPSRC Research Topic Classifications:
Human Communication in ICT
EPSRC Industrial Sector Classifications:
No relevance to Underpinning Sectors
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Summary on Grant Application Form
We argue that discrete state Hidden Markov Models are inadequate for modelling observations produced by underlying continuous processes: for example, the movement of the articulators during speech production. We propose to develop a continuous state Markov model. Our recent experience with articulatory measurement data suggests that one approach we can take is to let the (hidden) state represent articulator setting, and constrain the state behaviour by a linear, or possibly non-linear, dynamical system. With hidden observations of trajectories in the state space, training becomes simpler; at recognition time, the state space is hidden. Of course, the articulatory observations could be used only to initialise the model, with the state space being hidden during further training on acoustic-only data.
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