DeepFilterNet vs HushMic
DeepFilterNet
github.comHushMic
github.comSide by side
| Figure | DeepFilterNet | HushMic |
|---|---|---|
| Price from | Free | — |
| Free plan | Yes | — |
| Free trial | — | — |
| Open source | Yes | — |
| Windows | Yes | — |
| macOS | Yes | — |
| Linux | Yes | Yes |
| API | Yes | — |
| Self-hosted | Yes | — |
| Plans published | 2 | 0 |
| Spec score · AI Noise Cancellation Software | 9.0 (#1) | 7.2 (#16) |
| Distribution | The project provides precompiled binaries through its GitHub releases and a Python wheel through PyPI. | The project lists installation options for Debian or Ubuntu, Arch Linux, Fedora, NixOS, and AppImage. |
| Latency | The LADSPA plugin has a minimum latency of 20 ms from STFT processing, plus latency from the LADSPA host. | The project reports 80 ms of processing latency, plus PipeWire's own buffering. |
| License | The repository code is free and open source under either the MIT License or Apache License 2.0, at the user's option. | HushMic is available under either the MIT or Apache-2.0 license. |
| Noise suppression | Its command-line tool suppresses noise in WAV recordings. | It uses the DPDFNet model to reduce keyboard noise, fans, and background chatter from microphone audio. |
| Purpose | DeepFilterNet is a low-complexity speech enhancement framework for full-band 48 kHz audio using deep filtering. | HushMic provides real-time microphone noise suppression for Linux as a system-wide virtual microphone. |
Plans
In their own words
DeepFilterNet
DeepFilterNet is a free, open-source framework for speech enhancement on full-band 48 kHz audio, using deep filtering. Its command-line tool suppresses noise in WAV files, with 48 kHz as its only supported sampling rate. A LADSPA plugin provides real-time noise suppression and can be used with PipeWire filter chains to create a virtual microphone or audio output, including for VoIP apps such as Zoom or Discord. The plugin's minimum latency is 20 ms from STFT processing, plus any delay added by the LADSPA host. The Rust command-line tool defaults to DeepFilterNet2; the Python interface documents DeepFilterNet and DeepFilterNet2. An optional post-filter may slightly over-attenuate very noisy sections. The framework supports Linux, macOS and Windows, though training is tested only under Linux. The Python package installs as deepfilternet, and an optional train extra adds data-loading functionality for Linux training. Code is available under either the MIT License or Apache License 2.0.