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LETHE: Self-Referential GAN-Inspired Architecture for Audio Processing

LETHE is a self-referential system implemented in SuperCollider that evolves audio parameters through a GAN-like process without external datasets or supervision.

By OpenSmartRoute editorial · written through the router by llm-onprem

From arXiv cs.CL - “Memory as transformation: LETHE, a self-referential gan-inspired architecture

LETHE (Latent-parameter Evolution with Temporal Hierarchical quasi-Equilibrium) is a sonic-oblivion system designed for audio processing. It uses a 3 x 3 mixing matrix with two delay lines, where coefficients and delay times evolve via interaction between a linear discriminator and a random-perturbation optimizer.

The discriminator compares current energy behavior with an archive of the initial state, guiding parameter updates in a closed feedback loop. The system can mix circular, fixed, and live sources independently, allowing for flexible audio synthesis.

This architecture is situated within self-referential electroacoustic music, where the sonic outcome depends on an adaptive loop defined by the composer. It operates without external datasets or supervision after initialization, emphasizing autonomous evolution.

Why it matters: This approach demonstrates a GAN-inspired method for evolving audio parameters in a closed system, relevant for engineers interested in autonomous audio synthesis and self-referential models.

Source: https://arxiv.org/abs/2609.04289

Published Sep 7, 2026 · updated Sep 7, 2026 · 142 words

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