Exploring Approaches to Multi-Task Automatic Synthesizer Programming
Daniel A Faronbi (New York University); Iran R Roman (NYU); Juan P Bello (New York University)
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Automatic Synthesizer Programming is the task of transforming an audio signal that was generated from a virtual instrument, into the parameters of a sound synthesizer that would generate this signal. In the past, this could only be done for one virtual instrument. In this paper, we expand the current literature by exploring approaches to automatic synthesizer programming for multiple virtual instruments. Two different approaches to multi-task automatic synthesizer programming are presented. We find that the joint-decoder approach performs best. We also evaluate the performance of this model for different timbre instruments and different latent dimension sizes.