KAZOO: a sign language generation platform based on production rules

Braffort, Annelies; Filhol, Michael; Delorme, Maxime; Bolot, Laurence; Choisier, Annick; Verrecchia, Cyril

doi:10.1007/s10209-015-0415-2

Cited by 9 publications

(8 citation statements)

References 12 publications

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“…Current pipelines typically generate avatars based on a symbolic representation of the signed content prepared by a human author (e.g. [3,1,12,115,7]). When the avatar is generated as part of a translation system (e.g., [66,38]), an initial translation step converts spoken/written language into a symbolic representation of the sign language (as described in the previous section).…”

Section: Avatars and Computer Graphicsmentioning

confidence: 99%

Sign Language Recognition, Generation, and Translation

Bragg

Koller

Bellard

et al. 2019

The 21st International ACM SIGACCESS Conference on Computers and Accessibility

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284

130

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Developing successful sign language recognition, generation, and translation systems requires expertise in a wide range of fields, including computer vision, computer graphics, natural language processing, human-computer interaction, linguistics, and Deaf culture. Despite the need for deep interdisciplinary knowledge, existing research occurs in separate disciplinary silos, and tackles separate portions of the sign language processing pipeline. This leads to three key questions: 1) What does an interdisciplinary view of the current landscape reveal? 2) What are the biggest challenges facing the field? and 3) What are the calls to action for people working in the field? To help answer these questions, we brought together a diverse group of experts for a two-day workshop. This paper presents the results of that interdisciplinary workshop, providing key background that is often overlooked by computer scientists, a review of the state-of-the-art, a set of pressing challenges, and a call to action for the research community.Each group focused on the following questions:

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Section: Avatars and Computer Graphicsmentioning

confidence: 99%

Sign Language Recognition, Generation, and Translation

Bragg

Koller

Bellard

et al. 2019

The 21st International ACM SIGACCESS Conference on Computers and Accessibility

Self Cite

284

130

View full text Add to dashboard Cite

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“…APPENDIX 1: (de Araújo et al, 2013;Silva et al, 2012), 2: (V. López-Ludeña et al, 2014;Verónica López-Ludeña et al, 2013), 3: (López-Colino & Colás, 2012), 4: (J. Oh et al, 2014), 5: (Adamo-Villani et al, 2013), 6: (Al-Khalifa, 2011), 7: (De Martino et al, 2017), 8: (Ebling & Glauert, 2016;JASigning, 2012), 9: (Bouzid et al, 2016(Bouzid et al, , 2015Bouzid & Jemni, 2014, 2017, 10: (Li et al, 2014;Wang et al, 2010), 11: (Mehta et al, 2020), 12: (Hansen et al, 2018;Vcom3D, 2008), 13: (Punchimudiyanse & Meegama, 2017), 14: (Elliott et al, 2008;Kennaway et al, 2007;San-Segundo et al, 2012), 15: (Vesel & Robillard, 2013), 16: (Yousaf et al, 2018), 17: (Bouzid & Jemni, 2013a, 2013bGhoul & Jemni, 2009), 18: (Adamo-Villani et al, 2004), 19: (Adamo-Villani & Wilbur, 2010), 20: (Balayn et al, 2018), 21: (Braffort et al, 2016;Braffort & Dalle, 2008), 22: (Brega et al, 2014), 23: (Papadogiorgaki et al, 2005), 24: (Liu et al, 2009), 25: (Segouat & Braffort, 2009), 26: (Y. J. Oh et al, 2007), 27: (Ward et al, 2017), 28: (McDonald et al, 2016), 29: (Naert et al, 2020)...…”

Section: Statements Of Publication Ethicsmentioning

confidence: 99%

Visual Appearance Features of Sign Language Avatars

ATASOY,

ŞILBIR,

FİŞ ERÜMİT

et al. 2023

Kastamonu Education Journal

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Purpose: 3D Sign language avatars communicate with individuals in digital environments, like educational agents. However, while designing educational agents, the target group comes to the fore. In the literature, it is seen that the visual appearance features that should be considered in the creation of avatar designs are specified in diverse ways. Main goal of this study is to evaluate the sign language avatars’ visual appearance features in the literature and applications within the framework of educational agents. Design/Methodology/Approach: In this study, seventy-nine different sign language avatars’ images were evaluated within the framework of visual appearance features. Seven category and fifteen features were evaluated by four field experts through focus group discussions. Findings: In the evaluation, seven important categories were determined in avatar visual appearance. It is seen that the eye and head designs of avatars are generally designed in normal size. If an iconic design process is being carried out, eye, head, arm, and finger visual appearances should be designed larger than normal. If a realistic design process is carried out, eye, head, finger, palm, and arm visual appearances should be designed in normal sizes. Highlights: When designing sign language avatars, the upper body should be visible. In addition, what the target group will be affects the gender and iconicity of the avatar. Avatar should be designed simply so that individuals do not overload their visual channel. Also, different visual appearance features should be considered for iconic or realistic avatars. In addition to this, it is recommended that the hand and head sizes should be bigger than normal in order to understand the signs and non-manual signs more clearly.

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“…The Mexican Sign Language avatar presented by the authors [33] was created based on a combination of natural language processing (NLP) techniques with the use of programming engines (Unity) to create animation. Using the structured language model of AZee, Paul's Avatar [34] was created, which is a hybrid system animated mainly with hand-made keyframes, and Kazoo's virtual avatar [35], which generates content from French to sign language.…”

Section: Translation Of Spoken Languages Into Sign Languagesmentioning

confidence: 99%

Sign language interpreting - relationships between research in different areas - overview

Probierz,

Kozak,

Piasecki

et al. 2023

Annals of Computer Science and Information Systems

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Translation from the national language into sign language is an extremely important area of research and practice, which aims to ensure communication between deaf or hard of hearing people and the hearing community. The article provides an overview of the most important research on sign language interpretation conducted in various research areas. The latest scientific and theoretical achievements were presented, which contribute to a better understanding of the subject of sign language translation and the improvement of the quality of translation services. Our main goal is to identify outstanding areas of interdisciplinary research related to sign language translation and to identify links between these studies conducted in different areas. The conclusions of the article aim to broaden the knowledge and awareness of sign language translation and to identify areas that require further research and development. The work is linked to a project related to the application of machine learning in increasing accessibility for deaf people.

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KAZOO: a sign language generation platform based on production rules

Cited by 9 publications

References 12 publications

Sign Language Recognition, Generation, and Translation

Sign Language Recognition, Generation, and Translation

Visual Appearance Features of Sign Language Avatars

Sign language interpreting - relationships between research in different areas - overview

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