This repository implements the DTLN model for real-time speech enhancement, combining short-time Fourier transform with learned neural network bases to suppress noise in audio. The model uses a dual-signal transformation approach with under one million parameters, enabling real-time processing on resource-constrained devices like Raspberry Pi. It provides pretrained models in SavedModel, TF-lite, and ONNX formats for inference, along with training code.