Elastic Time: Dynamic Frame Rate Bottlenecks for Neural Audio Coding
Elastic Time introduces a method to make fixed-frame-rate autoencoders dynamic by learning a lightweight predictor. This predictor determines which latent frames can be skipped during inference, allowing for efficient rate control and frame skipping. The technique uses chunking based on latent predictability to achieve scalable models without external supervision.