An Algorithm for Determining Talker Location using a Linear Microphone Array and Optimal Hyperbolic Fit

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.