In acoustic emission (AE) measurement, the information of the arrival time is very important for event location, event identification and source mechanism analysis. Manual picks are time-consuming and sometimes subjective, especially in the case of large volumes of digital data. Various techniques have been presented in the literature and are routinely used in practice such as amplitude threshold, analysis of the long-term average/short-term average (LTA/STA), high-order statistics or artificial neural networks. A new automatic determination technique of the first arrival times of AE signals is presented for thin metal plates. Based on Akaike's information criterion, proposed algorithm of the first arrival detection uses a specific characteristic function, which is sensitive to change of frequency in contrast to others such as envelope of the signal. The approach is applied to data sets of three different tests. Reliable results show the potential of our approach.