A cost effective Sign Language to voice emulation system

Bhatnagar, Vidur S.; Magon, Rachit; Srivastava, Rashi; Thakur, Manish

doi:10.1109/ic3.2015.7346737

Cited by 10 publications

(9 citation statements)

References 9 publications

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“…The electronic system could recognize the ASL alphabet (20 out of 26 letters) and achieve an average accuracy of 96%. A holistic approach was also presented to develop a real-time smart glove system to convert static SL gestures into speech by using statistical template matching [ 3 ]. The “Sign Language Trainer & Voice Convertor” software acquired five custom-made flex sensors and one 3-axis ACC along with an Arduino Duemilanove Microcontroller Board.…”

Section: The Analysis Resultsmentioning

confidence: 99%

“…Customarily, a user interacts with the device through output devices, so the output devices play an important role in achieving the best performance of devices implemented in the field of SLR. The main device adopted by researchers as the output was the screen of computer [ 3 , 4 , 35 , 40 , 48 , 60 , 61 , 62 ]. Other devices attracting the attention of researchers are the liquid-crystal display (LCD) [ 12 , 35 , 57 , 63 ], speaker [ 38 , 46 , 54 , 64 ], or both [ 6 , 51 , 55 , 65 , 66 , 67 , 68 ].…”

Section: Methodsmentioning

confidence: 99%

“…The development of software for SLR systems is related to the methods used in the classification process to recognize gestures. One of the common direct methods to perform static posture recognition is prototype matching (also known as statistical template matching), which operates on the basis of statistics to determine closest match of acquired information values with pre-defined training samples called ‘templates’ [ 3 ]. In fact, this method is characterized by the lack of a need for complicated training processes or wide calibration, thus increasing its speed.…”

Section: Methodsmentioning

confidence: 99%

“…Furthermore, SL is unfamiliar to those who are not deaf and mute, and disabled people face serious difficulties in communicating with able individuals. This communication barrier adversely affects the lives and social relationships of deaf people [ 3 ]. Thus, dumb people need to use a translator device to communicate with able individuals.…”

Section: Introductionmentioning

confidence: 99%

“…However, not much work has been carried out in this direction due to the cost and computational overheads of the entire setup. Nevertheless, augmented reality systems produce promising results when used with hybrid tracking methodology [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

A Review on Systems-Based Sensory Gloves for Sign Language Recognition State of the Art between 2007 and 2017

Ahmed

Zaidan

et al. 2018

Sensors

176

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Loss of the ability to speak or hear exerts psychological and social impacts on the affected persons due to the lack of proper communication. Multiple and systematic scholarly interventions that vary according to context have been implemented to overcome disability-related difficulties. Sign language recognition (SLR) systems based on sensory gloves are significant innovations that aim to procure data on the shape or movement of the human hand. Innovative technology for this matter is mainly restricted and dispersed. The available trends and gaps should be explored in this research approach to provide valuable insights into technological environments. Thus, a review is conducted to create a coherent taxonomy to describe the latest research divided into four main categories: development, framework, other hand gesture recognition, and reviews and surveys. Then, we conduct analyses of the glove systems for SLR device characteristics, develop a roadmap for technology evolution, discuss its limitations, and provide valuable insights into technological environments. This will help researchers to understand the current options and gaps in this area, thus contributing to this line of research.

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Section: The Analysis Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A Review on Systems-Based Sensory Gloves for Sign Language Recognition State of the Art between 2007 and 2017

Ahmed

Zaidan

et al. 2018

Sensors

176

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A Review of Hand Gesture Recognition Systems Based on Noninvasive Wearable Sensors

Tchantchane,

Zhou,

Zhang

et al. 2023

Advanced Intelligent Systems

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Hand gesture, one of the essential ways for a human to convey information and express intuitive intention, has a significant degree of differentiation, substantial flexibility, and high robustness of information transmission to make hand gesture recognition (HGR) one of the research hotspots in the fields of human–human and human–computer or human–machine interactions. Noninvasive, on‐body sensors can monitor, track, and recognize hand gestures for various applications such as sign language recognition, rehabilitation, myoelectric control for prosthetic hands and human–machine interface (HMI), and many other applications. This article systematically reviews recent achievements from noninvasive upper‐limb sensing techniques for HGR, multimodal sensing fusion to gain additional user information, and wearable gesture recognition algorithms to obtain more reliable and robust performance. Research challenges, progress, and emerging opportunities for sensor‐based HGR systems are also analyzed to provide perspectives for future research and progress.

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