Biomimetic and flexible piezoelectric mobile acoustic sensors with multiresonant ultrathin structures for machine learning biometrics.

Flexible resonant acoustic sensors have attracted substantial attention as an essential component for intuitive human-machine interaction (HMI) in the future voice user interface (VUI). Several researches have been reported by mimicking the basilar membrane but still have dimensional drawback due to limitation of controlling a multifrequency band and broadening resonant spectrum for full-cover phonetic frequencies. Here, highly sensitive piezoelectric mobile acoustic sensor (PMAS) is demonstrated by exploiting an ultrathin membrane for biomimetic frequency band control. Simulation results prove that resonant bandwidth of a piezoelectric film can be broadened by adopting a lead-zirconate-titanate (PZT) membrane on the ultrathin polymer to cover the entire voice spectrum. Machine learning-based biometric authentication is demonstrated by the integrated acoustic sensor module with an algorithm processor and customized Android app. Last, exceptional error rate reduction in speaker identification is achieved by a PMAS module with a small amount of training data, compared to a conventional microelectromechanical system microphone.

Flexible Piezoelectric Acoustic Sensors and Machine Learning for Speech Processing.

Flexible piezoelectric acoustic sensors have been developed to generate multiple sound signals with high sensitivity, shifting the paradigm of future voice technologies. Speech recognition based on advanced acoustic sensors and optimized machine learning software will play an innovative interface for artificial intelligence (AI) services. Collaboration and novel approaches between both smart sensors and speech algorithms should be attempted to realize a hyperconnected society, which can offer personalized services such as biometric authentication, AI secretaries, and home appliances. Here, representative developments in speech recognition are reviewed in terms of flexible piezoelectric materials, self-powered sensors, machine learning algorithms, and speaker recognition.

Janus Graphene Liquid Crystalline Fiber with Tunable Properties Enabled by Ultrafast Flash Reduction.

Flash photothermal treatment via Xenon lamp with a broad wavelength spectrum can effectively remove oxygen functionalities and restore sp2 domains at graphitic carbon materials. The chemical composition and relevant structure formation of flash reduced graphene oxide liquid crystal (GOLC) fibers are investigated in accordance with flash irradiation conditions. Owing to the spatial controllability of reduction level via anisotropic flash irradiation, the mechanical properties and electrical conductivity of graphene fibers can be delicately counterbalanced to attain desired properties. High sensitivity humidity sensors can be fabricated from the flash reduced fibers demonstrating notably higher sensitivity over the thermally reduced counterparts. This ultrafast flash reduction holds great promise for multidimensional macroscopic GO based structures, enabling a wide range of potential applications, including textile electronics and wearable sensors.