Expressive Guitar Synthesis via Controllable Latent Flow Matching
Hsueh-Wei Fu, Yen-Tung Yeh, Yi-Hsuan Yang
Realistic guitar synthesis requires both audio fidelity and interpretable control over how notes are performed. The input timed MIDI events decide what is played but not how, leaving the continuous within-note decisions of guitar performance--such as pitch inflection and per-string articulation--unspecified. A model that directly maps MIDI to audio must therefore realize the performance implicitly, and users are left with limited control over the synthesized performance. We therefore propose a two-stage guitar synthesis pipeline that predicts editable, per-string $f_0$ and amplitude trajectories from timed note events and note-level dynamics, and renders them into audio using latent flow matching. Experimental results show that the proposed system outperforms a matched single-stage counterpart and DDSP-Guitar in control fidelity and perceived quality, while keeping the controls editable. Sound examples can be found online.
尚无 AI 解读，展示原文摘要