Drum Synthesis from Expressive Drum Grids via Neural Audio Codecs
Researchers have developed a new system that converts expressive drum grids, a detailed MIDI format, into realistic drum audio. This method utilizes a Transformer model to predict discrete codes from a neural audio codec, which are then decoded into sound. Experiments with codecs like EnCodec, DAC, and X-Codec show that the choice of audio representation significantly impacts the quality of the synthesized drums. The system was trained and evaluated on the E-GMD dataset, demonstrating codec-token prediction as a viable approach for percussive synthesis. AI
IMPACT Introduces a new method for generating realistic percussive audio from symbolic music representations, potentially impacting music production tools.