Swan

What it does

Every human voice carries an acoustic signature from the body that produced it. AI doesn't have a body. That difference is measurable. Humsana Swan analyzes audio across multiple acoustic signal domains to determine whether a voice is human or synthetically generated. Upload any audio file and get a determination in under two minutes. Built for fraud prevention teams, contact centers, and anyone working with voice authentication.

Swan detects synthetic voices by measuring the physics of speech, not by memorizing known deepfake models. Self-hostable and open source under AGPL-3.0.

Swan measures the biological physics of speech to tell a human voice from a synthetic one. It never needs retraining for the next voice-cloning tool. Swan reads the acoustic behavior that only biological phonation produces, then integrates it into a stable verdict. Jitter, spectral flatness, cross-band divergence, phase dispersion, and onset and offset transition morphology, frame by frame. A leaky-bucket integrator accumulates risk over time, so one noisy frame cannot flip the verdict. A forensic-style determination: human, synthetic, or inconclusive, with a stated behavioral driver. A JSON report plus readable dashboard and audit reports for every interaction. Ships with no API keys. You…from humsana.com

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