{"schema_version":1,"metadata":{"branch":"current","release":"7.9","architecture":"amd64","generated_at":"2026-09-09T04:04:41.004595+00:00","source_url":"https://cdn.openbsd.org/pub/OpenBSD/snapshots/packages/amd64/sqlports-7.55.tgz","source_sha256":"fcdbba1b9df747882aa9bab4af20ebec8dac10655069c90f1cd4145c06e1235e","package_count":12031,"source_kind":"sqlports"},"package":{"name":"rnnoise-0.2p0","path":"audio/rnnoise","url":"/packages/current/audio/rnnoise/","comment":"recurrent neural network for audio noise reduction","homepage":"https://jmvalin.ca/demo/rnnoise","maintainer":"Klemens Nanni <kn@openbsd.org>","description":"RNNoise is a noise suppression library based on a recurrent neural network.\nA description of the algorithm is provided in the following paper:\n\nJ.-M. Valin, A Hybrid DSP/Deep Learning Approach to Real-Time Full-Band Speech\nEnhancement, Proceedings of IEEE Multimedia Signal Processing (MMSP) Workshop,\narXiv:1709.08243, 2018.\nhttps://arxiv.org/pdf/1709.08243\n\nWhile it is meant to be used as a library, the code for a simple command-line\ntool is provided as an example. It operates on RAW 16-bit (machine endian) mono\nPCM files sampled at 48 kHz.\n","package_architecture":"amd64","stem":"rnnoise","readme":null,"dependencies":[{"path":"devel/metaauto","type":"build","package_spec":"","url":"/packages/current/devel/metaauto/"},{"path":"devel/autoconf/2.71","type":"build","package_spec":"","url":"/packages/current/devel/autoconf/2.71/"},{"path":"devel/automake/1.16","type":"build","package_spec":"","url":"/packages/current/devel/automake/1.16/"},{"path":"devel/libtool","type":"build","package_spec":"","url":"/packages/current/devel/libtool/"}],"reverse_dependencies":{"count":2,"url":"/packages/data/87/87927227088facee9614c61c944d97764d4495ab6679363234286a778334a802.json"},"categories":["audio"],"flavors":[],"only_for_architectures":[],"not_for_architectures":[]}}