Special issue: recent advances in sign language translation and avatar technology

Wolfe, Rosalee; Efthimiou, Eleni; Glauert, John; Hanke, Thomas; McDonald, John C.; Schnepp, Jerry

doi:10.1007/s10209-015-0412-5

Cited by 7 publications

(4 citation statements)

References 3 publications

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“…In parallel, researchers at DePaul University have been working on the issue of accessibility for deaf people, and the development of a signing avatar for the past 15 years. They also addressed machine translation from text to sign (Wolfe et al 2016).…”

Section: Sign Languagementioning

confidence: 99%

Computer-assisted sign language translation: a study of translators’ practice to specify CAT software

Kaczmarek

Filhol

2021

Machine Translation

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Professional Sign Language translators, unlike their text-to-text counterparts, are not equipped with computer-assisted translation (CAT) software. Those softwares are meant to ease the translators’ tasks. No prior study as been conducted on this topic, and we aim at specifying such a software. To do so, we based our study on the professional Sign Language translators’ practices and needs. The aim of this paper is to identify the necessary steps in the text-to-sign translation process. By filming and interviewing professionals for both objective and subjective data, we build a list of tasks and see if they are systematic and performed in a definite order. Finally, we reflect on how CAT tools could assist those tasks, how to adapt the existing tools to Sign Language and what is necessary to add in order to fit the needs of Sign Language translation. In the long term, we plan to develop a first prototype of CAT software for sign languages.

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Section: Sign Languagementioning

confidence: 99%

Computer-assisted sign language translation: a study of translators’ practice to specify CAT software

Kaczmarek

Filhol

2021

Machine Translation

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“…Image/vision approaches are not the only innovative ways of achieving ISL recognition. In [6] there was a special issue of the journal Universal Access in the Information Society on using avatars in SL recognition, a collected volume based on presentations given at the symposium Sign Language Translation and Avatar Technology (SLTAT) held in 2013. That included a paper [7] where the authors explored the effect of adding facial expressions which reveal emotional clues, into ISL recognition.…”

Section: Automatic Recognition Of Irish Sign Languagementioning

confidence: 99%

Recognising Irish Sign Language Using Electromyography

Galea

Smeaton

2019

2019 International Conference on Content-Based Multimedia Indexing (CBMI)

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Sign language is the non-verbal communication used by people with hearing and speaking impairments. The automatic recognition of sign languages is usually based on video analysis of the signer though this is difficult when considering different light levels or the surrounding environment. The work in this paper uses electromyography (EMG) and focuses on letters of the Irish Sign Language (ISL) alphabet. EMG is the recording of the electrical activity produced to stimulate movement in the skeletal muscles. We capture muscle signals and inertial movement data using the Thalmic MYO armband and, in real time, recognise the ISL alphabet. Our implementation is based on signal processing, feature extraction and machine learning. The only input required to translate the ISL gestures are EMG and movement data, thus our approach is usable in scenarios where using video for automatic recognition video is not possible.

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“…Taking this idea further, AI is being applied to overcome communication barriers of all kinds for all people, automatically translating audio and text between any language that is spoken, including sign languages (Ahmed et al, 2018;Wolfe et al, 2016). We are at the point where it is possible to translate, for example, British Sign Language into written Spanish and vice versa.…”

Section: Innovation For Inclusion Benefits Everyonementioning

confidence: 99%

Accessible Inclusive Learning: Futures

Coughlan¹,

Lister²,

Tai-Seale³

et al. 2019

Educational Visions: The Lessons From 40 Years of Innovation

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The previous chapter on Accessible Inclusive Learning: Foundations outlined some key approaches and challenges when conducting research that seeks to make learning accessible to all. Here, we explore newer trends that are directing our current research and practice in this area. These promising directions include devising models for global networks, the potential to collect and use data to understand learning experiences in new ways, and new opportunities arising through artificial intelligence. By exploring current and recent projects around these areas, we also highlight some emerging tensions. Finally, we return to thinking about how we conduct research, considering how concepts of bricolage and guerrilla research are important in our methodological palette.

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Special issue: recent advances in sign language translation and avatar technology

Cited by 7 publications

References 3 publications

Computer-assisted sign language translation: a study of translators’ practice to specify CAT software

Computer-assisted sign language translation: a study of translators’ practice to specify CAT software

Recognising Irish Sign Language Using Electromyography

Accessible Inclusive Learning: Futures

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