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In this work, we address the problem of musical timbre transfer, where thegoal is to manipulate the timbre of a sound sample from one instrument to matchanother instrument while preserving other musical content, such as pitch,rhythm, and loudness. In principle, one could apply image-based style transfertechniques to a time-frequency representation of an audio signal, but thisdepends on having a representation that allows independent manipulation oftimbre as well as high-quality waveform generation. We introduce TimbreTron, amethod for musical timbre transfer which applies "image" domain style transferto a time-frequency representation of the audio signal, and then produces ahigh-quality waveform using a conditional WaveNet synthesizer. We show that theConstant Q Transform (CQT) representation is particularly well-suited toconvolutional architectures due to its approximate pitch equivariance. Based onhuman perceptual evaluations, we confirmed that TimbreTron recognizablytransferred the timbre while otherwise preserving the musical content, for bothmonophonic and polyphonic samples.

TimbreTron: A WaveNet(CycleGAN(CQT(Audio))) Pipeline for Musical Timbre Transfer