© 2020 North Carolina State University.The aim of this work was to detect sounds providing evidence of the creation of drying defects and to correlate such data with drying quality. A further goal was to establish sound wave thresholds of ideal drying through the drying process by using an acoustic emission (AE) monitoring method. Thus, it is projected to decrease long drying times and also drying costs by reaching to ideal drying schedules. In this study, commercially preferred sessile oak and oriental beech structural lumbers were dried with three different schedules in a conventional kiln. The lumbers were "listened to" with AE sensors while drying according to the first two schedules, which were called protective and severe, respectively. AE events of the drying experiments were compared with ambient conditions and drying classes according to the standard of European Drying Group. The third drying schedule was optimized based on the AE peaks and applied. The results showed that ideal drying times were reduced up to 19% relative to the protective drying schedule, while obtaining the same drying quality for both species.