The internal availability of silent speech serves as a translator for people with aphasia and keeps human–machine/human interactions working under various disturbances.This paper develops a silent speech strategy to ...The internal availability of silent speech serves as a translator for people with aphasia and keeps human–machine/human interactions working under various disturbances.This paper develops a silent speech strategy to achieve all-weather,natural interactions.The strategy requires few usage specialized skills like sign language but accurately transfers high-capacity information in complicated and changeable daily environments.In the strategy,the tattoo-like electronics imperceptibly attached on facial skin record high-quality bio-data of various silent speech,and the machine-learning algorithm deployed on the cloud recognizes accurately the silent speech and reduces the weight of the wireless acquisition module.A series of experiments show that the silent speech recognition system(SSRS)can enduringly comply with large deformation(~45%)of faces by virtue of the electricitypreferred tattoo-like electrodes and recognize up to 110 words covering daily vocabularies with a high average accuracy of 92.64%simply by use of small-sample machine learning.We successfully apply the SSRS to 1-day routine life,including daily greeting,running,dining,manipulating industrial robots in deafening noise,and expressing in darkness,which shows great promotion in real-world applications.展开更多
基金supported by the National Natural Science Foundation of China(grant nos.51925503,U1713218)the Program for HUST Academic Frontier Youth Team.
文摘The internal availability of silent speech serves as a translator for people with aphasia and keeps human–machine/human interactions working under various disturbances.This paper develops a silent speech strategy to achieve all-weather,natural interactions.The strategy requires few usage specialized skills like sign language but accurately transfers high-capacity information in complicated and changeable daily environments.In the strategy,the tattoo-like electronics imperceptibly attached on facial skin record high-quality bio-data of various silent speech,and the machine-learning algorithm deployed on the cloud recognizes accurately the silent speech and reduces the weight of the wireless acquisition module.A series of experiments show that the silent speech recognition system(SSRS)can enduringly comply with large deformation(~45%)of faces by virtue of the electricitypreferred tattoo-like electrodes and recognize up to 110 words covering daily vocabularies with a high average accuracy of 92.64%simply by use of small-sample machine learning.We successfully apply the SSRS to 1-day routine life,including daily greeting,running,dining,manipulating industrial robots in deafening noise,and expressing in darkness,which shows great promotion in real-world applications.
