LALAL.AI vs NoiseTorch-ng

LALAL.AI uses AI to separate vocals and instrument stems, clean voice recordings, change or clone voices, and reduce echo and reverb. Its available stem types include vocals, instrumental, drums, bass, electric and acoustic guitar, piano, synthesizer, strings, and wind instruments. The web vocal remover accepts audio and video formats, including MP3, WAV, FLAC, MP4, and MOV. Fast Queue prioritizes processing, while Relaxed Queue processes as server capacity allows; both provide the same separation quality. Usage minutes are calculated by multiplying file length by the number of selected stem types. The desktop app supports Windows, macOS, and Ubuntu Linux, with batch processing for up to 20 files; Pro subscribers can optionally process locally offline. The API and VST plugin offer other ways to use the tools. The free Starter plan includes 10 Relaxed Queue minutes, but does not allow full downloads. Lite costs $7.50 a month billed annually.

NoiseTorch-ng is a free, open-source Linux application that reduces microphone noise in real time. It uses RNNoise and works with PulseAudio or PipeWire, creating a virtual “Filtered Microphone” for applications such as OBS, Mumble, and Discord. The project describes setup as a two-click process and distributes the app as a small, statically linked binary. A Voice Activation Threshold can be set as high as 95%, or set to 0% to dampen noise without deactivating the microphone. Optional output filtering routes applications through a virtual “Filtered Headphones” device. Microphone filtering adds 10 ms of inherent latency; output filtering is approximately 100 ms with PulseAudio. The project reports a suspected update-server and repository breach, says no malicious code was found, and says updates are retrieved from GitHub releases. GitHub reports no SECURITY.md file or published security advisories. Troubleshooting guidance, including how to collect debug logs, is in the project wiki. The latest listed release is v0.12.2, released June 17.