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In this paper, we present the performance of maximum likelihood (ML) estimator for number of multipath and SNR scenarios. Here the multipath acoustic channel output signal is modeled as a superposition of the delayed, attenuated, and filtered version of the stationary Gaussian stochastic input signal. Accuracy percentage (AP) performance measure has been used to characterize the performance of the estimator. The performance of the ML estimator is compared via computer simulation, using AP, with a generalized autocorrelation estimator (GAE) for different number of multipath and SNRs. Simulation results show that the performance of the ML estimator deteriorates as the number of multipath increase and/or SNR decreases, however its performance is superior to the GAE under the same circumstances.