RNNoise is a noise suppression library based on a recurrent neural network. A description of the algorithm is provided in the following paper: J.-M. Valin, A Hybrid DSP/Deep Learning Approach to Real-Time Full-Band Speech Enhancement, Proceedings of IEEE Multimedia Signal Processing (MMSP) Workshop, arXiv:1709.08243, 2018. https://arxiv.org/pdf/1709.08243.pdf An interactive demo is available at: https://jmvalin.ca/demo/rnnoise/ To compile, just type: % zig build While it is meant to be used as a library, a simple command-line tool is provided as an example. It operates on RAW 16-bit (machine endian) mono PCM files sampled at 48 kHz. It can be used as: ./zig-out/bin/rnnoise_demo <noisy speech> <output denoised> The output is also a 16-bit raw PCM file. The latest version of the source is available from https://gitlab.xiph.org/xiph/rnnoise . This is a fork that replaces the autotools build system with the Zig build system.