This paper addresses the problem of doubletalk detector calibration for acoustic echo cancellers in hands-free environments such as videoconferencing. A statistical model of a recently proposed doubletalk detector is used to show that optimal detection thresholds are dependent on the input signal and the adaptive filter error. A signal-adaptive algorithm is proposed for calculating an optimal threshold for arbitrary input signals and echo path environments. Simulation results verify the improvement in detection probability offered by the proposed algorithm compared to simple empirical calibration methods.