DeepFilterNet
7.5#1 in software composition analysis softwareFree planFree planAPILinuxmacOSSelf-hosted
VisitDeepFilterNet vs RNNoise
What both publish
| Fact | DeepFilterNet | RNNoise |
|---|---|---|
| Distribution | The project provides precompiled binaries through its GitHub releases and a Python wheel through PyPI. | The README says the GitHub repository is a convenience copy and identifies GitLab as the location of the latest source. |
| License | The repository code is free and open source under either the MIT License or Apache License 2.0, at the user's option. | The repository identifies its license as BSD-3-Clause. |
| Purpose | DeepFilterNet is a low-complexity speech enhancement framework for full-band 48 kHz audio using deep filtering. | RNNoise is a noise suppression library based on a recurrent neural network. |
| Security | The repository page shows a Security and quality tab but provides no security or compliance claims in the project information read. | The opened project pages state a software license but do not describe security certifications or compliance. |
| Training | Training expects datasets in HDF5 format, with a dataset configuration file for train, validation, and test sets. | Model training requires clean speech and noise data sampled at 48 kHz in 16-bit PCM format. |
DeepFilterNet plans
- DeepFilterNetFree
- Free and open sourceFree
RNNoise plans
- RNNoiseFree
Pick DeepFilterNet if…
It suits people seeking WAV noise suppression or a real-time noise-filtering path through LADSPA and PipeWire. Developers can also use the Python package or train with HDF5 datasets, with training tested only on Linux.
Pick RNNoise if…
RNNoise suits developers who want a Linux noise suppression library or command-line demo and can work with raw PCM audio. It may also suit those who need to load or train models using the specified audio format.