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EPSRC Reference: GR/G64916/01
Title: NOISE CANCELLATION FOR IN VEHICLE SPEECH RECOGNITION (SPEECH IN VEHICLES)
Principal Investigator: Elliott, Professor S
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department: Inst of Sound and Vibration Research
Organisation: University of Southampton
Scheme: Standard Research (Pre-FEC)
Starts: 09 June 1992 Ends: 08 October 1995 Value (£): 92,383
EPSRC Research Topic Classifications:
Human Communication in ICT
EPSRC Industrial Sector Classifications:
Creative Industries
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Panel History:  
Summary on Grant Application Form
To investigate microphone arrangements and signal processing techniques for clear speech reception in noisy vehicle interiors, with the aim of improving the performance of speech recognisers used in cars.(This work has been carried out in cooperation with Lotus Engineering and Marconi Speech and Information Systems, as part of JFIT project ITD3/1/3062).Progress:Initially, the use of single microphones for in-car speech reception was studied. Headset microphones were rejected as too inconvenient for the user. The best type of microphone and its positioning on the car interior were determined by measurements of speech-signal-to-noise-ratio (SSNR), using recordings of speech made in cars under various driving conditions. Several single-channel speech enhancement techniques were tested, using the in-car speech recordings as input data.The use of microphone arrays was studied next. The number of microphones and their positioning were considered, and several types of processing of their outputs were conceived and tested. Again, in-car speech recordings were used to measure the performances of the various array configurations. Performances were judged from both SSNRs and speech recognition error rates. This work has shown that considerable improvements in the performance of in-vehicle speech recognisers can be achieved, by correct design of the speech microphone(s), and by noise-reducing processing of the microphone output(s). The most promising processing techniques are based on adaptive filtering, using error criteria matched to the speech recognition algorithm. Development of these techniques is continuing.
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Organisation Website: http://www.soton.ac.uk