Apache RAT vs DeepFilterNet

Apache RAT is a free, open-source release-audit tool for checking software distributions, with particular attention to license headers. Version 0.18 provides a command-line client, an Ant task library, and a Maven plugin. You can include or exclude files using patterns, collections, pattern files, and file-size limits; apply approved-license lists; and produce plain, XML, missing-header, or unapproved-license reports. The Maven plugin can write target/rat.txt or add a report to a generated site. RAT can add Apache-2.0 headers and copyright notices to files allowed by configuration. XML license definitions are supported, and experienced users can extend matchers, formats, reports, and interfaces. It runs on Linux and is intended for self-hosted, on-premise use. Building requires Java 17, with Maven 3.9.13 or later recommended. Reports need interpretation and project-specific tuning, and heuristics can miss issues.

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.