Results: The information content, measured by fractal complexity, of ASL signing is shown to be greater than that of other upper body activities encountered in daily living.
ZARDOZ is a system which tackles the cross-modal machine-translation problem, translating speech and text into fluid sign language. We constructed a hardware prototype from off-the-shelf electronic components and used it to conduct 38 hours of sleep studies on 8 participants over a period of 30 days. Permission to make digital or hard copies of all or part of this work for personal or As demonstrated by the experimental results, WiFall yields 90 percent detection precision with a false alarm rate of 15 percent on average using a one-class SVM classifier in all testing scenarios. Inspired by previous works on motion detection with wearable, The sign languages used by deaf communities around the world represent a linguistic challenge that natural language researchers in A.I. American Sign Language Recognition Using RF Sensing, Deep Learning in the Era of Edge Computing: Challenges and Opportunities, Multi-channel Transformers for Multi-articulatory Sign Language Translation, Lightweight and Unobtrusive Data Obfuscation at IoT Edge for Remote Inference, Push the Limit of Acoustic Gesture Recognition, Expressive ASL Recognition using Millimeter-wave Wireless Signals, Application Informed Motion Signal Processing for Finger Motion Tracking Using Wearable Sensors, mmASL: Environment-Independent ASL Gesture Recognition Using 60 GHz Millimeter-wave Signals, A Lightweight and Inexpensive In-ear Sensing System For Automatic Whole-night Sleep Stage Monitoring, Long-term recurrent convolutional networks for visual recognition and description, Sequence to Sequence Learning with Neural Networks, WiFall: Device-Free Fall Detection by Wireless Networks, Glove-based hand gesture recognition sign language translator using capacitive touch sensor, Real-time American Sign Language Recognition using wrist-worn motion and surface EMG sensors, Hierarchical recurrent neural network for skeleton based action recognition, Personalized Speech recognition on mobile devices, BodyScan: Enabling Radio-based Sensing on Wearable Devices for Contactless Activity and Vital Sign Monitoring.
from English to ASL. Nurses are rarely familiar with ASL, and depression screening tools aren't easily translated, This paper describes a trilingual sign language dictionary (Japanese Sign Language and American Sign Language, and Korean Sign Language) which helps those who learn each sign language directly from their mother sign language.
In this paper we tackle the multi-articulatory sign language translation task and propose a novel multi-channel transformer architecture. Additionally, we minimize our memory footprint by using a single language model for both dictation and voice command domains, constructed using Bayesian interpolation.
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