AI & ML
CTAG-FX: Reinterpreting Synthesizer Parameter Spaces for Expressive Tone-Shaping Audio FX Design
arXiv cs.SD0 views
arXiv:2610.08182v1 Announce Type: cross Abstract: Recent text-guided audio FX research has focused on translating natural-language descriptions into parameters or chain configurations within existing FX systems. However, comparatively little attention has been paid to how the internal control space of an individual FX processor can itself be constructed. To address this gap, we propose CTAG-FX, which functionally reinterprets the roles of 78 parameters in a text-conditioned synthesizer configuration as controls of a tone-shaping FX processor. Each synthesizer configuration defines a fixed tone-shaping processor that can be repeatedly applied to new audio inputs rather than producing only a one-off rendered output. The text-conditioned synthesizer configurations are generated using A&R-CTAG, a retrieval-enhanced extension of CTAG. We evaluate CTAG-FX through signal-level analysis, together with a scrambled-mapping ablation in which parameter-to-control assignments are randomly permuted to assess the contribution of the proposed role assignment. Role-based mapping produces prompt-distinct spectral and nonlinear behavior, whereas scrambling reduces this prompt-specific differentiation and yields a more prompt-insensitive nonlinear profile. Overall, these results suggest that synthesizer parameter spaces can serve not only as sound-generation spaces but also as design resources for constructing new audio-FX control spaces. Audio samples are available at https://taylor3527eg-hub.github.io/ctag-fx-platform-demo/.
Source:https://arxiv.org/abs/2610.08182PreviousARIA: Audio-Driven Melody-Tone Relation Modeling for Cantonese Lyric AuthoringNextBeyond Perturbation Magnitude: Direction-Dependent Responses in Multimodal Geometric Representations
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