The edge tone is the sound generated when a planar jet of air from a nozzle comes into contact with a wedge and a number of physical conditions are met. Fluid dynamics equations were used to synthesize authentic edge tones without the need for complex computation. A real-time physically derived synthesis model was designed using the jet airspeed and nozzle exit-to-wedge geometry. We compare different theoretical equations used to predict the tone frequency. A decision tree derived from machine learning based on previously published experimental results was used to predict the correct mode of operation. Results showed an accurate implementation for mode selection and highlighted areas where operation follows or deviates from previously published data.
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