Security News > 2022 > April > Real-time voice concealment algorithm blocks microphone spying
Columbia University researchers have developed a novel algorithm that can block rogue audio eavesdropping via microphones in smartphones, voice assistants, and connected devices in general.
As real-world tests showed, the system can make speech impossible to discern by automatic speech recognition technology, no matter what software is used and the microphone's position.
Building upon deep neural network forecasting models applied to packet loss concealment, Columbia's researchers developed a new algorithm based on what they call a "Predictive attacks" model.
Their experiments tested the algorithm against various speech recognition systems, finding an overall induced word error rate of 80% when the whispers were deployed.
The scientists presented some realistic in-room tests, along with the resulting text identified by speech recognition systems in each case.
Notably, the experiments showed that smaller words like "The", "Our", and "They", are harder to mask, while longer words are generally easier for their algorithm to attack.