A recurrent neural network for real-time audio noise reduction.

RNNoise is a noise suppression library implemented as a recurrent neural network, designed for real-time audio processing. It uses a hybrid DSP/Deep Learning approach, enhancing speech quality by removing background noise from audio signals. The core architecture consists of a recurrent neural network trained on a diverse dataset of clean speech and various noise types. The library operates on RAW 16-bit mono PCM files sampled at 48 kHz, making it suitable for embedded systems and real-time communication applications. RNNoise provides a command-line tool for demonstration and can be integrated into larger audio processing pipelines. Its open-source nature and BSD-3-Clause license make it a flexible choice for developers seeking high-quality noise reduction solutions.
RNNoise is a noise suppression library implemented as a recurrent neural network, designed for real-time audio processing.
Explore all tools that specialize in real-time noise reduction. This domain focus ensures RNNoise delivers optimized results for this specific requirement.
Explore all tools that specialize in improving speech clarity. This domain focus ensures RNNoise delivers optimized results for this specific requirement.
Explore all tools that specialize in command-line tool usage. This domain focus ensures RNNoise delivers optimized results for this specific requirement.
Utilizes a recurrent neural network for adaptive noise modeling and suppression, offering superior performance compared to traditional DSP methods.
Designed for low-latency processing, making it suitable for real-time applications such as VoIP and conferencing.
Allows users to train the model on their own datasets to optimize performance for specific noise environments.
Optimized for x86 architectures with AVX2 or SSE4.1 instruction sets, enhancing processing speed.
Supports loading custom-trained models from binary files, allowing for flexibility and customization.
Download the source code from the GitHub repository.
Run `./autogen.sh` to generate the configure script.
Execute `./configure` to set up the build environment. Consider adding `--enable-x86-rtcd` for AVX2/SSE4.1 support.
Compile the library using `make`.
Optionally, install the library using `make install`.
Use the example tool with `./examples/rnnoise_demo <noisy speech> <output denoised>`.
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