Laser Metal Deposition (LMD) is an additive manufacturing process that enables the production of complex structures on existing parts. To reduce the use of costly and energy-intensive produced materials like titanium, these structures can be selectively deposited on favorable but differing substrate materials. However due to differing material characteristics, this results in a high defect potential. Extensive process parameter development and online process monitoring helps to minimize the impact of defect formation. Monitoring of airborne acoustic process emissions can be used to identify critical defects early during the process and gain information about process stability. Two approaches for in-process time-frequency monitoring of the acquired acoustic data were compared within this work: The short time Fast Fourier Transformation and the Continuous Wavelet Transformation. Performance criteria based on detected distinct defect events were defined to evaluate both approaches and define specifications for an Acoustic Emission In-Process Monitoring system.