AIMC Topic: Sign Language
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British Sign Language Recognition via Late Fusion of Computer Vision and Leap Motion with Transfer Learning to American Sign Language.
Sensors (Basel, Switzerland)
Sep 9, 2020
In this work, we show that a late fusion approach to multimodality in sign language recognition improves the overall ability of the model in comparison to the singular approaches of image classification (88.14%) and Leap Motion data classification (7...
Sign Language Recognition Using Wearable Electronics: Implementing k-Nearest Neighbors with Dynamic Time Warping and Convolutional Neural Network Algorithms.
Sensors (Basel, Switzerland)
Jul 11, 2020
We propose a sign language recognition system based on wearable electronics and two different classification algorithms. The wearable electronics were made of a sensory glove and inertial measurement units to gather fingers, wrist, and arm/forearm mo...
Dynamic Hand Gesture Recognition Based on a Leap Motion Controller and Two-Layer Bidirectional Recurrent Neural Network.
Sensors (Basel, Switzerland)
Apr 8, 2020
Dynamic hand gesture recognition is one of the most significant tools for human-computer interaction. In order to improve the accuracy of the dynamic hand gesture recognition, in this paper, a two-layer Bidirectional Recurrent Neural Network for the ...
Convolutional and recurrent neural network for human activity recognition: Application on American sign language.
PloS one
Feb 19, 2020
Human activity recognition is an important and difficult topic to study because of the important variability between tasks repeated several times by a subject and between subjects. This work is motivated by providing time-series signal classification...
Exploration of Chinese Sign Language Recognition Using Wearable Sensors Based on Deep Belief Net.
IEEE journal of biomedical and health informatics
Sep 16, 2019
In this paper, deep belief net (DBN) was applied into the field of wearable-sensor based Chinese sign language (CSL) recognition. Eight subjects were involved in the study, and all of the subjects finished a five-day experiment performing CSL on a ta...
American Sign Language Alphabet Recognition Using a Neuromorphic Sensor and an Artificial Neural Network.
Sensors (Basel, Switzerland)
Sep 22, 2017
This paper reports the design and analysis of an American Sign Language (ASL) alphabet translation system implemented in hardware using a Field-Programmable Gate Array. The system process consists of three stages, the first being the communication wi...
Ambient intelligence framework for real-time speech-to-sign translation.
Assistive technology : the official journal of RESNA
Feb 2, 2017
Sign language can be used to facilitate communication with and between deaf or hard of hearing (Deaf/HH). With the advent of video streaming applications in smart TVs and mobile devices, it is now possible to use sign language to communicate over wor...
On Human to Robot Skill Transfer for the Execution of Complex Tactile American Sign Language Tasks with a Bimanual Robot Platform.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
An estimated 0.2% of the world population is living with severe deafblindness with approximately ~1.5 million Americans using tactile American Sign Language (t-ASL) as their primary form of communication. To allow them to communicate without an in-pe...
Privacy-Preserving British Sign Language Recognition Using Deep Learning.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2022
Sign language is a means of communication between the deaf community and normal hearing people who use hand gestures, facial expressions, and body language to communicate. It has the same level of complexity as spoken language, but it does not employ...
Finger language recognition based on ensemble artificial neural network learning using armband EMG sensors.
Technology and health care : official journal of the European Society for Engineering and Medicine
Jan 1, 2018
BACKGROUND: Deaf people use sign or finger languages for communication, but these methods of communication are very specialized. For this reason, the deaf can suffer from social inequalities and financial losses due to their communication restriction...
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