Intuition enables experienced machine operators to detect production errors and to identify their specific sources. A prominent example in machining are chatter marks caused by machining vibrations. The operators assessment, if the process runs stable or not, is not exclusively based on technical parameters such as rotation frequency, tool diameter, or the number of teeth. Because the human ear is a powerful feature extraction and classification device, this study investigates to what degree the hearing sensation influences the operators decision making. A steel machining process with a design of experiments (DOE)-based variation of process parameters was conducted on a milling machine. Microphone and acceleration sensors recorded machining vibrations and machine operators documented their hearing sensation via survey sheet. In order to obtain the optimal dataset for calculating various psychoacoustic characteristics, a principle component analysis was conducted. The subsequent correlation analysis of all sensor data and the operator information suggest that psychoacoustic characteristics such as tonality and loudness are very good indicators of the process quality perceived by the operator. The results support the application of psychoacoustic technology for machine and process monitoring.