Text to Sign Language Translation System

Goyal, Lalit; Goyal, Vishal

doi:10.4018/ijse.2016070104

Cited by 7 publications

(3 citation statements)

References 15 publications

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“…As reported in Shah et al (2022), numerous researchers worked toward translating English text into ISL. The authors (Goyal and Goyal, 2016b) demonstrated translation systems used to convert the text into ISL. Wazalwar and Shrawankar (2017) describes the use of a rule-based system to convert ISL text to English text using the Lookahead Left-to-Right (LALR) parser.…”

Section: Related Workmentioning

confidence: 99%

An approach based on deep learning for Indian sign language translation

Mistree

Thakor²,

Bhatt³

2022

IJICC

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PurposeAccording to the Indian Sign Language Research and Training Centre (ISLRTC), India has approximately 300 certified human interpreters to help people with hearing loss. This paper aims to address the issue of Indian Sign Language (ISL) sentence recognition and translation into semantically equivalent English text in a signer-independent mode.Design/methodology/approachThis study presents an approach that translates ISL sentences into English text using the MobileNetV2 model and Neural Machine Translation (NMT). The authors have created an ISL corpus from the Brown corpus using ISL grammar rules to perform machine translation. The authors’ approach converts ISL videos of the newly created dataset into ISL gloss sequences using the MobileNetV2 model and the recognized ISL gloss sequence is then fed to a machine translation module that generates an English sentence for each ISL sentence.FindingsAs per the experimental results, pretrained MobileNetV2 model was proven the best-suited model for the recognition of ISL sentences and NMT provided better results than Statistical Machine Translation (SMT) to convert ISL text into English text. The automatic and human evaluation of the proposed approach yielded accuracies of 83.3 and 86.1%, respectively.Research limitations/implicationsIt can be seen that the neural machine translation systems produced translations with repetitions of other translated words, strange translations when the total number of words per sentence is increased and one or more unexpected terms that had no relation to the source text on occasion. The most common type of error is the mistranslation of places, numbers and dates. Although this has little effect on the overall structure of the translated sentence, it indicates that the embedding learned for these few words could be improved.Originality/valueSign language recognition and translation is a crucial step toward improving communication between the deaf and the rest of society. Because of the shortage of human interpreters, an alternative approach is desired to help people achieve smooth communication with the Deaf. To motivate research in this field, the authors generated an ISL corpus of 13,720 sentences and a video dataset of 47,880 ISL videos. As there is no public dataset available for ISl videos incorporating signs released by ISLRTC, the authors created a new video dataset and ISL corpus.

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Section: Related Workmentioning

confidence: 99%

An approach based on deep learning for Indian sign language translation

Mistree

Thakor²,

Bhatt³

2022

IJICC

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“…Sign language synthesis and visualization is an area that tackles visualization issues of sign languages and the creation of signed speech. This field researches and develops means of realistically ''spoken'' sign languages, using video and image sequences or digital characters [5].…”

Section: Introductionmentioning

confidence: 99%

Technological Solutions for Sign Language Recognition: A Scoping Review of Research Trends, Challenges, and Opportunities

et al. 2022

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Habitat for the Elderly, and CA19121 Network on Privacy-Aware Audio-and Video-Based Applications for Active and Assisted Living, supported by COST (European Cooperation in Science and Technology). COST (European Cooperation in Science and Technology) is a funding agency for research and innovation networks. Our Actions help connect research initiatives across Europe and enable scientists to grow their ideas by sharing them with their peers. This boosts their research, career and innovation. www.cost.eu.

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“…Fig. 1 Letters A-F Recent research of sign language generation focus on using signing avatars [9,12,26]. These avatars are able to display facial expressions.…”

Section: Introductionmentioning

confidence: 99%

A Novel Web Based Dictionary Framework for Indian Sign Language

Joy¹,

Balakrishnan

Sreeraj³

2021

SN COMPUT. SCI.

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Getting to know sign equivalent of a spoken language word is not that easy when accessing a web page. In many cases, people search multimedia sign dictionaries to find the sign equivalent. ISLHelper is a browser plugin that can display Indian Sign Language(ISL) signs within a web page without navigating away from it. Both qualitative and quantitative analysis were conducted to measure the usability of the developed application. The plugin can work with Firefox web browser and can be extended to display signs corresponding to different languages. The application currently has 1600 words and is available as a plugin in the Firefox Browser add-ons centre. Average SUS score obtained for the study is 85.7, which is considered to be good. This indicates that perceived usability of ISLHelper application is favourable for the participants. Feedback from the participants suggests that the application is found to be helpful for learning ISL Signs.

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Text to Sign Language Translation System

Cited by 7 publications

References 15 publications

An approach based on deep learning for Indian sign language translation

An approach based on deep learning for Indian sign language translation

Technological Solutions for Sign Language Recognition: A Scoping Review of Research Trends, Challenges, and Opportunities

A Novel Web Based Dictionary Framework for Indian Sign Language

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