WiMi Releases Silent Speech Recognition

WiMi Hologram Cloud has launched a silent speech recognition system based on multifeatured signal perception technology that can convert electrical signals from body or laryngeal vocal cord movements into speech through silent reading or body movement recognition.

WiMi developed this system to enable silent speech recognition by using limb movements or facial electromyography (EMG) in a holographic augmented reality environment. First, the system acquires holographic EMG signal data or vocal fold vibration signal data presented by users' faces or limbs and then preprocesses the two data types obtained separately. After feature extraction and fusion, the system uses deep learning to perform recognition sequentially and finally sends the recognized command results to the receiving device or the controlled device.

To improve the system's accuracy for signal classification at a distance, WiMi developed a deep neural network-based classification method using an SSR system with fEMG in a holographic environment. The technique uses similar fEMG data previously collected from other individuals and then transformed by holographic dynamic position distortion. The system performs voiced or unvoiced speech recognition and acquires brain information by collecting surface EMG signals from limb or vocal muscles, processing and recognizing them.

WiMi said in a statement that it expects this system to contribute to the further development of speech recognition technology and provide new ideas and methods for speech recognition.