Hydaway introduces real-time enterprise audio deepfake detection

Hydaway Digital Corp. has launched Streaming Audio Detection inside its RealityChek platform for enterprise clients. The feature works “like Shazam” for analyzing live audio streams to identify synthetic or manipulated audio.

Conventional audio deepfake detection solutions work on recorded files or post-event review. But now voice-cloning attacks happen during live phone calls, call center interactions, executive impersonation attempts, media events, and voice-authenticated identity checks.

“Most organizations are still thinking about this problem in terms of static file uploads and post-hoc analysis, but the real damage is happening in real time, over the phone, in live broadcasts, in executive impersonation calls,” says Karl Kottmeier, chief executive officer at Hydaway.

In such environments, a detection result that arrives after the call or broadcast has ended may be too late to stop the fraud. Hydaway says that RealityChek can move audio deepfake detection closer to the moment of risk, giving enterprises a way to flag synthetic speech before it reaches its target or completes the deception.

“Our Streaming Audio Detection brings the speed of real-time analysis to a problem that has never had a real-time solution before. Think of it as a lie detector for live audio and one that never sleeps,” Kottmeier adds.

Specialized models enable instant analysis

Hydaway’s deepfake audio detection technology is built on continuous forensic analysis of a live audio stream. The company says the system looks for spectral patterns, prosodic markers, compression artifacts and generative model signatures associated with AI-synthesized speech.

At a high level, these signals help the system assess if a voice sounds and behaves like natural human speech or shows traces commonly with synthetic voice generation and cloning tools.

Spectral patterns can point to unusual frequency behavior in the audio signal. Prosodic markers relate to the rhythm, pitch, stress, and timing of speech. Compression artifacts can reveal distortions introduced during recording, transmission, or manipulation.

Hydaway says real-time audio forensics are challenging because the detection architecture must make reliable decisions from partial data at low latency without sacrificing accuracy. The system uses specialized models tuned to artifacts and signatures from current voice synthesis and cloning technologies.

The launch fits into Hydaway’s effort to move RealityChek beyond static content checks and into real-time trust decisions. Hydaway recently released its Liveness Checker to verify whether a person in a video stream or submission is a live, real human being or an AI-generated deepfake, synthetic avatar, or pre-recorded replay attack.

Article Topics

AI fraud  |  deepfake detection  |  deepfakes  |  RealityChek  |  synthetic voice  |  voice biometrics