cargo-audit vs DeepFilterNet
cargo-audit
rustsec.orgDeepFilterNet
github.comSide by side
| Figure | cargo-audit | DeepFilterNet |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | Yes |
| Windows | — | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | — | Yes |
| Self-hosted | — | Yes |
| Plans published | 1 | 2 |
| Spec score · Software Composition Analysis Software | 7.9 (#25) | 8.9 (#1) |
| License | The cargo-audit crates are licensed under either Apache License 2.0 or MIT, at the user's option. | The repository code is free and open source under either the MIT License or Apache License 2.0, at the user's option. |
| Purpose | Audits Cargo.lock files for crates with security vulnerabilities reported to the RustSec Advisory Database. | DeepFilterNet is a low-complexity speech enhancement framework for full-band 48 kHz audio using deep filtering. |
Plans
In their own words
cargo-audit
cargo-audit has no write-up on Specifiction yet; its figures are above.
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.