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Word recognition using multisensor speech input in high ambient noise

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4 Author(s)
Roucos, S. ; BBN Laboratories, Cambridge, MA ; Viswanathan, V. ; Henry, C. ; Schwartz, R.

We present a method for word recognition with input speech transduced simultaneously by several sensors in high levels of broadband acoustic background noise. In prior work on single-input multisensor systems, limited success in machine recognition was achieved by linearly combining multiple sensor signals to yield a robust estimate of the speech signal in the presence of noise. In this paper, we demonstrate that improved recognition results are obtained by using all available sensor signals jointly as a vector, which preserves information from all sensors, as input to the decision process. We report on multisensor configurations using close-talking pressure-gradient microphones and accelerometers placed at the throat and nose of the speaker. The recognition error rates obtained by using the joint output vector are 45% lower than the error rates obtained with the best constituent sensor in the multisensor system; single-input multisensor systems, on the other hand, produce error rates that are about equal to the error rates obtained with the best constituent sensor.

Published in:

Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '86.  (Volume:11 )

Date of Conference:

Apr 1986