New voice recognition system offers 99% accuracy even in noisy envrionment

As the traditional solid-based sensors are less effective in noisy environments and susceptible to unwanted disturbances, researchers at Beijing Forestry University have reported a self-filtering liquid acoustic sensor for accurate voice recognition and better human-machine interaction. These sensors are based on a reconfigurable magnetic liquid called Permanent Fluidic Magnet (PFM) with high remanent magnetization. This means the liquid behaves like a permanent magnet, boosting the liquid’s magnetic properties. Scientists have integrated liquid acoustic sensors with machine learning algorithms, which improves voice recognition accuracy by 99%, even in loud surroundings.