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SMDT: Selective Memory-Augmented Neural Document Translation ...
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Neural Network-Enabled Flexible Pressure and Temperature Sensor with Honeycomb-like Architecture for Voice Recognition
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In: Sensors (Basel) (2022)
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Abstract:
Flexible pressure sensors have been studied as wearable voice-recognition devices to be utilized in human-machine interaction. However, the development of highly sensitive, skin-attachable, and comfortable sensing devices to achieve clear voice detection remains a considerable challenge. Herein, we present a wearable and flexible pressure and temperature sensor with a sensitive response to vibration, which can accurately recognize the human voice by combing with the artificial neural network. The device consists of a polyethylene terephthalate (PET) printed with a silver electrode, a filament-microstructured polydimethylsiloxane (PDMS) film embedded with single-walled carbon nanotubes and a polyimide (PI) film sputtered with a patterned Ti/Pt thermistor strip. The developed pressure sensor exhibited a pressure sensitivity of 0.398 kPa [Formula: see text] in the low-pressure regime, and the fabricated temperature sensor shows a desirable temperature coefficient of resistance of 0.13% [Formula: see text] C in the range of 25 [Formula: see text] C to 105 [Formula: see text] C. Through training and testing the neural network model with the waveform data of the sensor obtained from human pronunciation, the vocal fold vibrations of different words can be successfully recognized, and the total recognition accuracy rate can reach 93.4%. Our results suggest that the fabricated sensor has substantial potential for application in the human-computer interface fields, such as voice control, vocal healthcare monitoring, and voice authentication.
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Keyword:
Communication
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URL: http://www.ncbi.nlm.nih.gov/pubmed/35161507 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8840666/ https://doi.org/10.3390/s22030759
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Neural Mechanisms of Hearing Recovery for Cochlear-Implanted Patients: An Electroencephalogram Follow-Up Study
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In: Front Neurosci (2021)
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Variability in the analysis of a single neuroimaging dataset by many teams
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In: ISSN: 0028-0836 ; EISSN: 1476-4679 ; Nature ; https://www.hal.inserm.fr/inserm-02914443 ; Nature, Nature Publishing Group, 2020, 582 (7810), pp.84-88. ⟨10.1038/s41586-020-2314-9⟩ (2020)
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FGraDA: A Dataset and Benchmark for Fine-Grained Domain Adaptation in Machine Translation ...
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Multi-Criteria Decision-Making Method Based on Simplified Neutrosophic Linguistic Information with Cloud Model ...
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Multi-Criteria Decision-Making Method Based on Simplified Neutrosophic Linguistic Information with Cloud Model ...
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Additional file 1: of Dog vaccination with EgM proteins against Echinococcus granulosus ...
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Additional file 1: of Dog vaccination with EgM proteins against Echinococcus granulosus ...
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Multi-Criteria Decision-Making Method Based On Simplified Neutrosophic Linguistic Information With Cloud Model ...
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Multi-Criteria Decision-Making Method Based On Simplified Neutrosophic Linguistic Information With Cloud Model ...
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A Component-Based Vocabulary-Extensible Sign Language Gesture Recognition Framework
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