Abstract
We derive a probabilistic formulation, based upon Bayes' rule, for the acoustic localization problem. The resulting formula is shown to be closely related to the energy of a conventionally beamformed signal. We then present a close approximation to both which is much faster to compute — by two orders of magnitude with our experimental setup. The fast algorithm is essentially a generalization of approaches based upon time delay estimates (TDE's), by applying the principle of least commitment. Experiments on real signals demonstrate accurate localization in noisy, reverberant environments (less than 3 dB SNR) several times faster than real time.
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