Name Date Size #Lines LOC

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doc/H25-Apr-2025-1914

examples/H25-Apr-2025-6131

include/H25-Apr-2025-11533

m4/H25-Apr-2025-322284

src/H25-Apr-2025-15,28914,249

training/H25-Apr-2025-239170

AUTHORSH A D25-Apr-202537 21

Android.bpH A D25-Apr-2025666 3128

COPYINGH A D25-Apr-20251.5 KiB3226

METADATAH A D25-Apr-2025391 2019

MODULE_LICENSE_BSDHD25-Apr-20250

Makefile.amH A D25-Apr-20253.6 KiB13183

READMEH A D25-Apr-2025596 2215

TRAINING-READMEH A D25-Apr-2025311 126

autogen.shH A D25-Apr-2025227 115

configure.acH A D25-Apr-20253.7 KiB130101

rnnoise-uninstalled.pc.inH A D25-Apr-2025320 1411

rnnoise.pc.inH A D25-Apr-2025293 1512

update_versionH A D25-Apr-20252.3 KiB6630

README

1RNNoise is a noise suppression library based on a recurrent neural network.
2
3To compile, just type:
4% ./autogen.sh
5% ./configure
6% make
7
8Optionally:
9% make install
10
11While it is meant to be used as a library, a simple command-line tool is
12provided as an example. It operates on RAW 16-bit (machine endian) mono
13PCM files sampled at 48 kHz. It can be used as:
14
15./examples/rnnoise_demo <noisy speech> <output denoised>
16
17The output is also a 16-bit raw PCM file.
18
19The latest version of the source is available from
20https://gitlab.xiph.org/xiph/rnnoise .  The github repository
21is a convenience copy.
22

TRAINING-README

1(1) cd src ; ./compile.sh
2
3(2) ./denoise_training signal.raw noise.raw count > training.f32
4
5    (note the matrix size and replace 500000 87 below)
6
7(3) cd training ; ./bin2hdf5.py ../src/training.f32 500000 87 training.h5
8
9(4) ./rnn_train.py
10
11(5) ./dump_rnn.py weights.hdf5 ../src/rnn_data.c ../src/rnn_data.h
12