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a084434e14
Fork point for agent-zed. Editor core retained; AI/telemetry/cloud layers to be ripped and replaced per FORK_MAP.md. Co-Authored-By: Claude Opus 4.8 <[email protected]> |
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| examples | ||
| models | ||
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| Cargo.toml | ||
| LICENSE-GPL | ||
| README.md | ||
Real time streaming audio denoising using a Dual-Signal Transformation LSTM Network for Real-Time Noise Suppression.
Trivial to build as it uses the native rust Candle crate for inference. Easy to integrate into any Rodio pipeline.
# use rodio::{nz, source::UniformSourceIterator, wav_to_file};
let file = std::fs::File::open("clips_airconditioning.wav")?;
let decoder = rodio::Decoder::try_from(file)?;
let resampled = UniformSourceIterator::new(decoder, nz!(1), nz!(16_000));
let mut denoised = denoise::Denoiser::try_new(resampled)?;
wav_to_file(&mut denoised, "denoised.wav")?;
Result::Ok<(), Box<dyn std::error::Error>>
Acknowledgements & License
The trained models in this repo are optimized versions of the models in the breizhn/DTLN. These are licensed under MIT.
The FFT code was adapted from Datadog's dtln-rs Repo also licensed under MIT.