Sign Language Communities

Meulder, Maartje De; Krausneker, Verena; Turner, Graham; Conama, John Bosco

doi:10.1057/978-1-137-54066-9_8

Cited by 16 publications

(9 citation statements)

References 67 publications

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“…Apart from robotic motion, there are additional factors that have fueled the negative attitude of deaf communities toward signing avatars. In many cases, deaf signers identify themselves as members of a minority group to which language is the main carrier of cultural heritage and identity, rather than persons with a disability (De Meulder et al, 2019). As such, they need to continuously struggle with policy making issues on local, national, or even global level to establish their right to use their SL for all communication purposes and have the right to face a hearing majority (Branson and Miller, 1998) who is not familiar with SL user communities' reality.…”

Section: Technological and Societal Backgroundmentioning

confidence: 99%

What about synthetic signing? A methodology for signer involvement in the development of avatar technology with generative capacity

et al. 2022

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Although signing avatar technology seems to be the only option currently available to serve sign language (SL) display in the context of applications which demand generative capacity from the part of the technology like in machine translation to SL, signing avatars have not yet been accepted by signers' communities. One major factor for this rejection is the feeling that technology is developed without the involvement of its actual users. Aiming to invite the signers' community into the process of signing avatar development, we have designed the shell methodological framework for signer-informed technology which is implemented as on-line surveys addressed to signer communities of different SLs. The surveys are communicated via focused on-line questionnaires with content of signing avatar performance that allows rating of various aspects of the produced SL synthetic signing by human signers. Here we report on the first survey application with content from the Greek Sign Language (GSL). The analysis of the obtained results is 2-fold: it highlights the significance of signer involvement and the provided feedback in the technological development of synthetic signing; in parallel it reveals those aspects of the survey setup that need fine-tuning before its next distribution cycles. The implementation of the first on-line survey can be found in: https://sign.ilsp.gr/slt-survey/.

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Section: Technological and Societal Backgroundmentioning

confidence: 99%

What about synthetic signing? A methodology for signer involvement in the development of avatar technology with generative capacity

et al. 2022

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“…The relation between all those languages, both spoken and signed, is a hierarchical one, involving deeply rooted issues of power. Society tends to categorize languages into first-, second-and third-class languages (De Meulder et al 2019;Eckert and Rickford 2002;Woodbury, n.d.;Trovato 2013). A first-class language is one with the most prestige, such as those that belong to past colonizing powers (English, Spanish, etc.…”

Section: The Linguistic Situation On the Islandmentioning

confidence: 99%

A ‘new’ Village Sign Language: structural properties of LSOR in Puerto Rico?

Benedicto¹,

Rivera-Castillo²

2021

FEAST

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In this preliminary analysis, we describe the use of the signing space in morphosyntactic processes in Orocovis Sign Language (LSOR), a Village Sign Language shared as the medium of communication between Deaf and hearing members of a rural community in Puerto Rico. It has been passed on from generation to generation, and exhibits an extended and absolute use of the signing space, and grammatical features like agreement, aspectual marking, and classifiers. These preliminary results contribute to shape the emerging typological complexity in the area of Village Sign Languages.

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“…Alongside increasing globalization and exchange of information come persistent need for means of translation. There are between 6000 and 7000 natural languages around the world [1]. Human translation is slow and expensive, so, machine translation plays an important role in reducing language barriers and facilitating communication between people speaking different languages [2].…”

Section: Introductionmentioning

confidence: 99%

Residual Information Flow for Neural Machine Translation

2022

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Automatic machine translation plays an important role in reducing language barriers between people speaking different languages. Deep neural networks (DNN) have attained major success in diverse research fields such as computer vision, information retrieval, language modelling, and recently machine translation. Neural sequence-to-sequence networks have accomplished noteworthy progress for machine translation. Inspired by the success achieved by residual connections in different applications, in this work, we introduce a novel NMT model that adopts residual connections to achieve better performing automatic translation. Evaluation of the proposed model has shown an improvement in translation accuracy by 0.3 BLEU compared to the original model, using an ensemble of 5 LSTMs. Regarding training time complexity, the proposed model saves about 33% of the time needed by the original model to train datasets of short sentences. Deeper neural networks of the proposed model have shown a good performance in dealing with the vanishing/exploding problems. All experiments have been performed over NVIDIA Tesla V100 32G Passive GPU and using the WMT14 English-German translation task.

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Sign Language Communities

Cited by 16 publications

References 67 publications

What about synthetic signing? A methodology for signer involvement in the development of avatar technology with generative capacity

What about synthetic signing? A methodology for signer involvement in the development of avatar technology with generative capacity

A ‘new’ Village Sign Language: structural properties of LSOR in Puerto Rico?

Residual Information Flow for Neural Machine Translation

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