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Details of Grant 

EPSRC Reference: GR/L78680/01
Title: SPEECH RECOGNITION USING ARTICULATORY DATA
Principal Investigator: Hardcastle, Professor WJ
Other Investigators:
Isard, Mr S
Researcher Co-Investigators:
Project Partners:
Department: Speech and Hearing Sciences
Organisation: Queen Margaret University Edinburgh
Scheme: Standard Research (Pre-FEC)
Starts: 01 May 1998 Ends: 30 April 2001 Value (£): 216,787
EPSRC Research Topic Classifications:
Human Communication in ICT
EPSRC Industrial Sector Classifications:
No relevance to Underpinning Sectors
Related Grants:
Panel History:  
Summary on Grant Application Form
We propose to gather a multispeaker articulatory/acoustic speech database (British version of TIMIT) suitable for training a state-of-the-art ASR system. The articulatory data will be captured directly and simultaneously with the acoustic recording using a purpose built studio which incorporates an Electromagnetic Articulograph, an Electropalatograph and Larybogoraph. Parameters derived from the articulatory data will be used as input features to a standard triphone model, mixture density HMM recogniser and the word error rate on a multispeaker recognition task compared with that of the same system using traditional acoustic features. Once an articulatory feature set has been determined which demonstrates an improved recognition score, a supervised learning process will be employed so that the articulatory parameters may be estimated from the acoustic signal. This nonlinear transform of the acoustic data into a feature space that is atuned to the dynamic constraints imposed by human speech production should lead to a recogniser that is more robust in its ability to handle inter and intra speaker variability.
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Further Information:  
Organisation Website: http://www.qmu.ac.uk