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cs.SD2026
AutoSynth: Learning to Generate Editable Synthesizer Programs from Audio and Text
Tristan Wu, Daniel Chin, Liwei Lin +2
Audio generation models can translate natural-language descriptions into sound, but their outputs are typically waveforms. Their audio quality is constrained by audio compression,…
cs.SD2026
DDSynth-RL: Audio Synthesizer Inversion via Discrete Diffusion with Reinforcement Learning
Tristan Wu, Daniel Chin, Junan Zhang +3
Synthesizer inversion is challenging for two main reasons: 1) Distinct parameter configurations can produce perceptually similar sounds. 2) Parameter-space losses often fail to ref…