Voice deepfakes are becoming more realistic and accessible every day. PulmoForge detects them in real-time.
Dataset + training pipeline restructure underway
Rebuilding the dataset from only commercially viable datasets. Earlier contaminated Datasets are being removed from the training pipeline.
New better datasets are being added and outdated/flawed datasets are being removed for maximum effects from the training pipeline.
Full retraining of model under a cleaner pipeline and different techniques. Beta version will be released after this.
Earlier iterations included synthetic speech sources that were not fully verified for licensing compatibility or distribution consistency — introducing risk of dataset contamination and evaluation drift. The system is being reset to a clean training baseline so that the next public model reflects results we can fully stand behind.
| System | Meeting audio | Compression trained | Status |
|---|---|---|---|
| PulmoForge | ✓ Zoom + Opus | ✓ Yes | ⟳ Rebuilding |
| Legacy detectors | ✗ Mostly lab audio | ✗ Rarely | Modern gen AI bypasses |
| Enterprise fraud tools | ✓ Phone systems | Unknown | Closed platforms |
Most voice fraud systems were not built around Zoom compression pipelines. PulmoForge was trained directly on compressed meeting audio.
Opus compression removes many high-frequency artifacts that traditional detectors rely on. PulmoForge was trained directly on codec-degraded speech to learn synthesis patterns that survive real-world meeting conditions.
Built for actual calls — not clean studio audio.
PulmoForge is in a controlled rebuild. The public beta model is being retrained on a clean, fully verified dataset. Free beta access will be available once the new model passes internal evaluation — join the waitlist to be notified first.