Self-powered acoustic sensor boosts AI recognition

Technology News |
By Nick Flaherty

The team at KAIST led by Professor Keon Jae Lee from the Department of Material Science and Engineering buiolt a flexible piezoelectric membrane by mimicking the basilar membrane in the human cochlear. Resonant frequencies vibrate corresponding regions of the trapezoidal piezoelectric membrane, which converts voice to electrical signal with a highly sensitive self-powered acoustic sensor.

Multiple sensor channels were integrated in a single self-powered chip with a size of 1.5 × 3 cm..The sensor is twice as sensitive as condensor-based sensors and allows for more abundant voice information compared to conventional acoustic sensors, which can detect minute sounds from farther distances. In addition, the acoustic sensor can achieve a 97.5% speaker recognition rate using a machine learning algorithm, reducing the error rate by over 75 percent

The team enhanced the speaker recognition system by replacing the existing hardware with the flexible piezoelectric acoustic sensor, and further software improvement of the piezoelectric acoustic sensor will significantly increase the speaker and voice recognition rate in diverse environments.

 “Highly sensitive self-powered acoustic sensors for speaker recognition can be used for personalized voice services such as smart home appliances, AI secretaries, always-on IoT, biometric authentication, and FinTech,” said Professor Lee.

The papers on “Basilar Membrane-Inspired Self-Powered Acoustic Sensor” and “Machine Learning-based Acoustic Sensor for Speaker Recognition” were published in Nano Energy.

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