Desert Ant Labs · On-device diarization

Who

Who is an on-device speaker diarization model from Desert Ant Labs that labels who spoke when in audio and video, returning per-speaker turns with timestamps. It is aimed at podcasts, interviews, calls and meetings. Speakers are numbered in order of first appearance, and overlapping speech is marked for both people. Recordings of any length are handled by processing five-minute sections in one pass each, then matching voices across sections with a speaker-verification network and clustering. The developers say a 50-minute interview takes 3 seconds on a MacBook Pro. Reported diarization error rates include 12.6% on AMI meetings, 8.4% on VoxConverse (up to 4 speakers) and 17.5% on VoxConverse (2-21 speakers). They are higher on far-field sets, such as 41.1% on DiPCo and 39.9% on CHiME-6. It runs on the Neural Engine on Apple platforms, through LiteRT on Linux, Windows and Android, and through WebAssembly in the browser and Node, with an ONNX build also available. The Core ML download is 81MB at float16 or 42MB with 8-bit weights. Weights are v0.3.4, status is beta, and the licence is Desert Ant Labs' own source-available licence.