TAPE: Learning General Audio Effect Representations

TAPE (Transformations of Audio Parameter Embeddings) is a system that learns to infer the signal‑processing chain applied to a reference audio recording and then applies the same chain to new material. It uses an encoder to map the processed reference to an embedding that a differentiable DSP decoder translates into editable parameters for equalization, compression, waveshaping, a residual network, and reverberation. Compared to prior methods, TAPE achieves lower spectral error while being 275× faster than exhaustive search and can run causally in real time on 128‑sample buffers.

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