A Distributed Learning Approach for Controlled Grammar Transfer using Structure–Timbre Disentangled Audio Synthesis
This research article introduces a probabilistic framework for controlled grammar transfer in audio synthesis, tackling the issue of blending audio styles in a way that is both interpretable and disentangled. Current methods either depend on low-level feature matching or use neural models that mix structural and timbra...