An algorithm for determining talker location using a linear microphone array and optimal hyperbolic fit

  • Authors:
  • Harvey F. Silverman

  • Affiliations:
  • -

  • Venue:
  • HLT '90 Proceedings of the workshop on Speech and Natural Language
  • Year:
  • 1990

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Abstract

One of the problems for all speech input is the necessity for the talker to be encumbered by a head-mounted, hand-held, or fixed position microphone. An intelligent, electronically-aimed unidirectional microphone would overcome this problem. Array techniques hold the best promise to bring such a system to practicality. The development of a robust algorithm to determine the location of a talker is a fundamental issue for a microphone-array system. Here, a two-step talker-location algorithm is introduced. Step 1 is a rather conventional filtered cross-correlation method; the cross-correlation between some pair of microphones is determined to high accuracy using a some-what novel, fast interpolation on the sampled data. Then, using the fact that the delays for a point source should fit a hyperbola, a best hyperbolic fit is obtained using nonlinear optimization. A method which fits the hyperbola directly to peak-picked delays is shown to be far less robust than an algorithm which fits the hyperbola in the cross-correlation space. An efficient, global nonlinear optimization technique, Stochastic region Contraction (SRC) is shown to yield highly accurate (>90%), and computationally efficient, results for a normal ambient.