Graphene‐based dual‐function acoustic transducers for machine learning‐assisted human–robot interfaces
Hao Sun,
Xin Gao,
Liang‐Yan Guo,
Lu‐Qi Tao,
Zi Hao Guo,
Yangshi Shao,
Tianrui Cui,
Yi Yang,
Xiong Pu,
Tian‐Ling Ren
Affiliations
Hao Sun
Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist) Tsinghua University Beijing People's Republic of China
Xin Gao
School of Computer Science & Technology Beijing Institute of Technology Beijing People's Republic of China
Liang‐Yan Guo
State Key Laboratory of Power Transmission Equipment and System Security and New Technology, School of Electrical Engineering Chongqing University Chongqing People's Republic of China
Lu‐Qi Tao
School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing People's Republic of China
Zi Hao Guo
CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro‐nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems Chinese Academy of Sciences Beijing People's Republic of China
Yangshi Shao
CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro‐nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems Chinese Academy of Sciences Beijing People's Republic of China
Tianrui Cui
Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist) Tsinghua University Beijing People's Republic of China
Yi Yang
Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist) Tsinghua University Beijing People's Republic of China
Xiong Pu
CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro‐nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems Chinese Academy of Sciences Beijing People's Republic of China
Tian‐Ling Ren
Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist) Tsinghua University Beijing People's Republic of China
Abstract Human–robot interface (HRI) electronics are critical for realizing robotic intelligence. Here, we report graphene‐based dual‐function acoustic transducers for machine learning‐assisted human–robot interfaces (GHRI). The GHRI functions both an artificial ear through the triboelectric acoustic sensing mechanism and an artificial mouth through the thermoacoustic sound emission mechanism. The success of the integrated device is also attributed to the multifunctional laser‐induced graphene, as either triboelectric materials, electrodes, or thermoacoustic sources. By systematically optimizing the structure parameters, the GHRI achieves high sensitivity (4500 mV Pa–1) and operating durability (1 000 000 cycles and 60 days), capable of recognizing speech identities, emotions, content, and other information in the human speech. With the assistance of machine learning, 30 speech categories are trained by a convolutional neural network, and the accuracy reaches 99.66% and 96.63% in training datasets and test datasets. Furthermore, GHRI is used for artificial intelligence communication based on recognized speech features. Our work shows broad prospects for the development of robotic intelligence.
