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EPSRC Reference:
GR/T04649/01
Title:
Streamed Models for Automatic Speech Recognition
Principal Investigator:
King, Professor S
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department:
Centre for Speech Technology Research
Organisation:
University of Edinburgh
Scheme:
Advanced Fellowship (Pre-FEC)
Starts:
01 January 2005
Ends:
31 December 2009
Value (£):
254,954
EPSRC Research Topic Classifications:
Human Communication in ICT
EPSRC Industrial Sector Classifications:
Creative Industries
Related Grants:
Panel History:
Panel Date
Panel Name
Outcome
19 Apr 2004
ICT Fellowships 2004 - ARF Interview Panel
Deferred
18 Mar 2004
ICT Fellowships 2004 Sift Panel
Deferred
Summary on Grant Application Form
Current automatic speech recognition techniques involve probabilistic models (hidden Markov models) which do not reflect much of our knowledge of how speech is produced: they are not speech-specific. The proposal is to investigate the wider class of models of which the hidden Markov model is a member, to find more appropriate models of speech. These will model speech more faithfully and it is hoped they will therefore perform speech recognition more accurately.The proposal is timely, because it builds on recent advances in this field in terms of the mathematical understanding of these models and the algorithms required to work with them; software tools are now available which will allow a rapid start to the proposed programme of research. The proposed work will be carried out within the Centre forSpeech Technology Research at the University of Edinburgh, which has a strong track record of innovative work in speech technology; the proposer also has a strong track record in novel approaches to automatic speech recognition.The resources required are modest since the computational infrastructure is already in place, and the Centre for Speech Technology Research will provide support, both in terms of technical support staff and colleagues working on highly related projects. This makes the proposed work very likely to produce results quickly
Key Findings
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Project URL:
Further Information:
Organisation Website:
http://www.ed.ac.uk