Automatic Sign Language Translation to Improve Communication

Oliveira, Tiago; Escudeiro, Paula; Escudeiro, Nuno; Rocha, Emanuel; Barbosa, F. P. Maciel

doi:10.1109/educon.2019.8725244

Cited by 26 publications

(10 citation statements)

References 11 publications

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“…Interpreters who speak sign language are also essential during sporting events. Their presence fosters a sense of inclusion and equal engagement, enabling deaf people to fully grasp the essence of crowd discussions, announcements, and cheers [83][84][85].…”

Section: Applications Of Sign Language Translatorsmentioning

confidence: 99%

A Survey of Advancements in Real-Time Sign Language Translators: Integration with IoT Technology

2023

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Real-time sign language translation systems are of paramount importance in enabling communication for deaf and hard-of-hearing individuals. This population relies on various communication methods, including sign languages and visual techniques, to interact with others. While assistive technologies, such as hearing aids and captioning, have improved their communication capabilities, a significant communication gap still exists between sign language users and non-users. In order to bridge this gap, numerous sign language translation systems have been developed, encompassing sign language recognition and gesture-based controls. Our research aimed to analyze the advancements in real-time sign language translators developed over the past five years and their integration with IoT technology. By closely examining these technologies, we aimed to attain a deeper comprehension of their practical applications and evolution in the domain of sign language translation. We analyzed the current literature, technical reports, and conference papers on real-time sign language translation systems. Our results offer insights into the current state of the art in real-time sign language translation systems and their integration with IoT technology. We also provide a deep understanding of the recent developments in sign language translation technology and the potential for their fusion with Internet of Things technology to improve communication and promote inclusivity for the deaf and hard-of-hearing population.

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Section: Applications Of Sign Language Translatorsmentioning

confidence: 99%

A Survey of Advancements in Real-Time Sign Language Translators: Integration with IoT Technology

2023

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“…For feature extraction, the system uses a deep CNN, and a bidirectional RNN is used to understand the sequence of motions. Ying Xie et al [12] suggested Deaf and dumb people will get benefit from a computer vision-based approach to interpret sign language. This method converts sign language into text, making it easier for the people to interact.…”

Section: Related Workmentioning

confidence: 99%

Deep Learning Based Indian Sign Language Words Identification System

Jeyasheeli¹,

Indumathi

2021

Recent Trends in Intensive Computing

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In Indian Population there is about 1 percent of the people are deaf and dumb. Deaf and dumb people use gestures to interact with each other. Ordinary humans fail to grasp the significance of gestures, which makes interaction between deaf and mute people hard. In attempt for ordinary citizens to understand the signs, an automated sign language identification system is proposed. A smart wearable hand device is designed by attaching different sensors to the gloves to perform the gestures. Each gesture has unique sensor values and those values are collected as an excel data. The characteristics of movements are extracted and categorized with the aid of a convolutional neural network (CNN). The data from the test set is identified by the CNN according to the classification. The objective of this system is to bridge the interaction gap between people who are deaf or hard of hearing and the rest of society.

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“…Sign language interpreter plays a significant role to bridge the gap between hearing impaired and hearing people. Bi-directional communication in the machine translation, system comprises of two sub-systems: (i) receives the speech or text as input and generates the corresponding gesture as output, (ii) captures the gesture as input and generates the text or speech as output [8,84]. As per Ethnologue 2019, there are 7111 spoken languages and near about 200 sign languages in the world [3,45].…”

Section: Introductionmentioning

confidence: 99%

An automatic machine translation system for multi-lingual speech to Indian sign language

Dhanjal

Singh

2021

Multimed Tools Appl

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Sign language (SL) is the best suited communication medium for hearing impaired people. Even with the advancement of technology, there is a communication gap between the hearing impaired and hearing people. The aim of this research work is to bridge this gap by developing an automatic system that translates the speech to Indian Sign Language using Avatar (SISLA). The whole system works in three phases: (i) The first phase includes the speech recognition (SR) of isolated words for English, Hindi and Punjabi in speaker independent environment (ii) The second phase translates the source language into Indian Sign Language (ISL) (iii) HamNoSys based 3D avatar represents the ISL gestures. The four major implementation modules for SISLA include: requirement analysis, data collection, technical development and evaluation. The multi-lingual feature makes the system more efficient. The training and testing speech sample files for English (12,660, 4218), Hindi (12,610, 4211) and Punjabi (12,600, 4193) have been used to train and test the SR models. Empirical results of automatic machine translation show that the proposed trained models have achieved the minimum accuracy of 91%, 89% and 89% for English, Punjabi and Hindi respectively. Sign language experts have also been used to evaluate the sign error rate through feedback. Future directions to enhance the proposed system using non-manual SL features along with the sentence level translation has been suggested. Usability testing based on survey results confirm that the proposed SISLA system is suitable for education as well as communication purpose for hearing impaired people.

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Automatic Sign Language Translation to Improve Communication

Cited by 26 publications

References 11 publications

A Survey of Advancements in Real-Time Sign Language Translators: Integration with IoT Technology

A Survey of Advancements in Real-Time Sign Language Translators: Integration with IoT Technology

Deep Learning Based Indian Sign Language Words Identification System

An automatic machine translation system for multi-lingual speech to Indian sign language

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