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Including Signed Languages in Natural Language Processing

Paper · 2021 · Kayo Yin, Amit Moryossef, Julie Hochgesang et al.

Summary

This position paper argues that signed languages, used by up to 70 million deaf people across roughly 200 languages, are largely ignored by NLP. Sign Language Processing (SLP) has mostly been driven by computer vision and rarely draws on linguistic structure. The authors first survey the linguistic features that models must handle: phonology built from manual and non-manual parameters, simultaneous information channels, spatial referencing, classifiers and role shift. They then review the weaknesses of current SLP systems. A small experiment illustrates the data problem. A gloss-to-text Transformer that does reasonably well on the narrow-domain RWTH-PHOENIX-Weather 2014T benchmark almost collapses on the open-domain Public DGS Corpus. The paper proposes a roadmap with four parts: standardized tokenization that loses little information, linguistically informed extensions of core NLP tools, collection of large and realistic signed data, and Deaf community leadership throughout the research process. The paper matters because it presents SLP both as a gap in accessibility and as a way to understand language in the visual modality.

Key points

  • The authors' gloss-to-text Transformer scores 22.17 BLEU on RWTH-PHOENIX-Weather 2014T but only 3.2 BLEU on the Public DGS Corpus. This gap shows that current benchmarks overstate real-world readiness.
  • The Public DGS Corpus contains about 50 hours of natural signing by 330 native signers from different German regions. It is annotated with glosses, HamNoSys and German translations.
  • Annotating signed video can take up to 600 minutes of work per minute of footage. The authors therefore call for tools that automate or crowdsource parts of annotation, such as boundary detection, feature extraction and gloss suggestions.
  • The authors criticize intrusive approaches, such as sensor gloves, and systems that only recognize fingerspelling or isolated signs. Deaf communities widely reject these as oversimplifying sign grammar and as audist.
  • The paper recommends long-term partnerships with Deaf researchers and users, including involving signers in reviewing ACL papers on signed languages.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

 Institutions

🎓Carnegie Mellon UniversityPittsburgh · United States365 works · 158,048 citations🔬Allen Institute for Artificial IntelligenceSeattle · United States219 works · 89,712 citations🎓Bar-Ilan UniversityRamat Gan · Israel118 works · 21,077 citations🎓University of PittsburghPittsburgh · United States38 works · 21,591 citations

Also on the byline: Gallaudet University.

📚 Shelves 7 Computer Science · 9,086 works Artificial Intelligence · 8,889 works Arts and Humanities · 9,296 works Language and Linguistics · 9,206 works Psychology · 798 works Developmental and Educational Psychology · 260 works Human-Computer Interaction · 61 works

Cite

Cite as Kayo Yin, Amit Moryossef, Julie Hochgesang, Yoav Goldberg and Malihe Alikhani. 2021. Including Signed Languages in Natural Language Processing. Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers).

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.18653/v1/2021.acl-long.570

@inproceedings{yin2021including,
  title = {{Including Signed Languages in Natural Language Processing}},
  author = {Kayo Yin, Amit Moryossef, Julie Hochgesang, Yoav Goldberg and Malihe Alikhani},
  booktitle = {Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)},
  year = {2021},
  doi = {10.18653/v1/2021.acl-long.570},
  url = {https://doi.org/10.18653/v1/2021.acl-long.570}
}

References

112 references, 4 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

  1. Nikolas Adaloglou, Theocharis Chatzis, Ilias Papastratis, Andreas Stergioulas, Georgios Th Papadopoulos, Vassia Zacharopoulou, George J Xydopoulos, Klimnis Atzakas, Dimitris Papazachariou, and Petros Daras. 2020. A comprehensive study on sign language recognition methods. arXiv preprint arXiv:2007.1… — [arXiv:2007.12530](https://arxiv.org/abs/2007.12530) find
  2. Waleed Ammar, Dirk Groeneveld, Chandra Bhagavatula, Iz Beltagy, Miles Crawford, Doug Downey, Jason Dunkelberger, Ahmed Elgohary, Sergey Feldman, Vu Ha, Rodney Kinney, Sebastian Kohlmeier, Kyle Lo, Tyler Murray, Hsu-Han Ooi, Matthew Peters, Joanna Power, Sam Skjonsberg, Lucy Wang, Chris Wilhelm, Zhen… our card
  3. Naveen Arivazhagan, Ankur Bapna, Orhan Firat, Dmitry Lepikhin, Melvin Johnson, Maxim Krikun, Mia Xu Chen, Yuan Cao, George Foster, Colin Cherry, et al. 2019. Massively multilingual neural machine translation in the wild: Findings and challenges. arXiv preprint arXiv:1907.05019. our card
  4. Tadas Baltrušaitis, Chaitanya Ahuja, and Louis-Philippe Morency. 2018. Multimodal machine learning: A survey and taxonomy. IEEE transactions on pattern analysis and machine intelligence, 41(2):423–443. find
  5. Robbin Battison. 1978. Lexical borrowing in American sign language. ERIC. find
  6. Ursula Bellugi and Susan Fischer. 1972. A comparison of sign language and spoken language. Cognition, 1(2-3):173–200. find
  7. Brita Bergman. 1979. Signed Swedish. National Swedish Board of Education [Skolöverstyr.]:. find
  8. Louise de Beuzeville. 2008. Pointing and verb modification: the expression of semantic roles in the auslan corpus. In Workshop Programme, page 13. Citeseer. find
  9. Steven Bird. 2020. Decolonising speech and language technology. In Proceedings of the 28th International Conference on Computational Linguistics, pages 3504–3519, Barcelona, Spain (Online). International Committee on Computational Linguistics. our card
  10. Julian Bleicken, Thomas Hanke, Uta Salden, and Sven Wagner. 2016. Using a language technology infrastructure for German in order to anonymize German Sign Language corpus data. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16), pages 3303– 3306, Porto… find
  11. Mark Borg and Kenneth P Camilleri. 2019. Sign language detection ”in the wild” with recurrent neural networks. In ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages 1637–1641. IEEE. find
  12. Danielle Bragg, Oscar Koller, Mary Bellard, Larwan Berke, Patrick Boudreault, Annelies Braffort, Naomi Caselli, Matt Huenerfauth, Hernisa Kacorri, Tessa Verhoef, Christian Vogler, and Meredith Ringel Morris. 2019. Sign language recognition, generation, and translation: An interdisciplinary perspecti… find
  13. Diane Brentari. 2011. Sign language phonology. The handbook of phonological theory, pages 691–721. find
  14. Diane Brentari and Carol Padden. 2001. A language with multiple origins: Native and foreign vocabulary in american sign language. Foreign vocabulary in sign language: A cross-linguistic investigation of word formation, pages 87–119. find
  15. Hannah Bull, Michèle Gouiffès, and Annelies Braffort. 2020. Automatic segmentation of sign language into subtitle-units. In European Conference on Computer Vision, pages 186–198. Springer. find
  16. Necati Cihan Camgöz, Simon Hadfield, Oscar Koller, Hermann Ney, and Richard Bowden. 2018. Neural sign language translation. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 7784–7793. find
  17. Necati Cihan Camgöz, Oscar Koller, Simon Hadfield, and Richard Bowden. 2020a. Multi-channel transformers for multi-articulatory sign language translation. In European Conference on Computer Vision, pages 301–319. find
  18. Necati Cihan Camgöz, Oscar Koller, Simon Hadfield, and Richard Bowden. 2020b. Sign language transformers: Joint end-to-end sign language recognition and translation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 10023–10033. find
  19. Z. Cao, G. Hidalgo Martinez, T. Simon, S. Wei, and Y. A. Sheikh. 2019. Openpose: Realtime multi-person 2d pose estimation using part affinity fields. IEEE Transactions on Pattern Analysis and Machine Intelligence. find
  20. Yu Chen, Chunhua Shen, Xiu-Shen Wei, Lingqiao Liu, and Jian Yang. 2017. Adversarial posenet: A structure-aware convolutional network for human pose estimation. In Proceedings of the IEEE International Conference on Computer Vision, pages 1212–1221. find
  21. Necati Cihan Camgöz, Simon Hadfield, Oscar Koller, Hermann Ney, and Richard Bowden. 2018. Neural sign language translation. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 7784–7793. find
  22. Kearsy Cormier, Sandra Smith, and Zed Sevcikova-Sehyr. 2015. Rethinking constructed action. Sign Language & Linguistics, 18(2):167–204. find
  23. Onno Crasborn, R Bank, I Zwitserlood, E Van der Kooij, E Ormel, J Ros, A Schüller, A de Meijer, M van Zuilen, YE Nauta, et al. 2016. Ngt signbank. Nijmegen: Radboud University, Centre for Language Studies. find
  24. Onno A Crasborn and IEP Zwitserlood. 2008. The corpus ngt: an online corpus for professionals and laymen. find
  25. Runpeng Cui, Hu Liu, and Changshui Zhang. 2017. Recurrent convolutional neural networks for continuous sign language recognition by staged optimization. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 7361–7369. find
  26. NCSLGR Databases. 2007. Volumes 2–7. find
  27. Philippe Dreuw, Thomas Deselaers, Daniel Keysers, and Hermann Ney. 2006. Modeling image variability in appearance-based gesture recognition. In ECCV workshop on statistical methods in multi-image and video processing, pages 7–18. find
  28. Paul G Dudis. 2004. Body partitioning and real-space blends. Cognitive linguistics, 15(2):223–238. find
  29. Sarah Ebling, Necati Cihan Camg ö z, Penny Boyes Braem, Katja Tissi, Sandra Sidler-Miserez, Stephanie Stoll, Simon Hadfield, Tobias Haug, Richard Bowden, Sandrine Tornay, Marzieh Razavi, and Mathew Magimai-Doss. 2018. SMILE Swiss German sign language dataset. In Proceedings of the Eleventh Internat… find
  30. Michael Erard. 2017. Why sign-language gloves don’t help deaf people. The Atlantic, 9. find
  31. Iva Farag and Heike Brock. 2019. Learning motion disfluencies for automatic sign language segmentation. In ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages 7360–7364. IEEE. find
  32. Jordan Fenlon, Kearsy Cormier, and Adam Schembri. 2015. Building bsl signbank: The lemma dilemma revisited. International Journal of Lexicography, 28(2):169–206. find
  33. Jordan Fenlon, Adam Schembri, and Kearsy Cormier. 2018. Modification of indicating verbs in british sign language: A corpus-based study. Language, 94(1):84–118. find
  34. Lucinda Ferreira-Brito. 1984. Similarities & differences in two brazilian sign languages. Sign language studies, 42:45–56. find
  35. Jens Forster, Christoph Schmidt, Oscar Koller, Martin Bellgardt, and Hermann Ney. 2014. Extensions of the sign language recognition and translation corpus rwth-phoenix-weather. In LREC, pages 1911–1916. find
  36. Binyam Gebrekidan Gebre, Peter Wittenburg, and Tom Heskes. 2013. Automatic sign language identification. In 2013 IEEE International Conference on Image Processing, pages 2626–2630. IEEE. find
  37. Neil S Glickman and Wyatte C Hall. 2018. Language deprivation and deaf mental health. Routledge. find
  38. Rıza Alp Güler, Natalia Neverova, and Iasonas Kokkinos. 2018. Densepose: Dense human pose estimation in the wild. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 7297–7306. find
  39. Eva Gutierrez-Sigut, Brendan Costello, Cristina Baus, and Manuel Carreiras. 2016. Lse-sign: A lexical database for spanish sign language. Behavior Research Methods, 48(1):123–137. find
  40. Wyatte C Hall, Leonard L Levin, and Melissa L Anderson. 2017. Language deprivation syndrome: A possible neurodevelopmental disorder with sociocultural origins. Social psychiatry and psychiatric epidemiology, 52(6):761–776. find
  41. Thomas Hanke, Marc Schulder, Reiner Konrad, and Elena Jahn. 2020. Extending the Public DGS Corpus in size and depth. In Proceedings of the LREC2020 9th Workshop on the Representation and Processing of Sign Languages: Sign Language Resources in the Service of the Language Community, Technological Cha… find
  42. Raychelle Harris, Heidi M Holmes, and Donna M Mertens. 2009. Research ethics in sign language communities. Sign Language Studies, 9(2):104– 131. find
  43. Saad Hassan, Larwan Berke, Elahe Vahdani, Longlong Jing, Yingli Tian, and Matt Huenerfauth. 2020. An isolated-signing RGBD dataset of 100 American Sign Language signs produced by fluent ASL signers. In Proceedings of the LREC2020 9th Workshop on the Representation and Processing of Sign Languages: S… find
  44. Jie Huang, Wengang Zhou, Qilin Zhang, Houqiang Li, and Weiping Li. 2018. Video-based sign language recognition without temporal segmentation. In Proceedings of the AAAI Conference on Artificial Intelligence, volume 32. find
  45. Tom Humphries, Poorna Kushalnagar, Gaurav Mathur, Donna Jo Napoli, Carol Padden, Christian Rathmann, and Scott Smith. 2016. Avoiding linguistic neglect of deaf children. Social Service Review, 90(4):589–619. find
  46. Reiner Konrad, Thomas Hanke, Gabriele Langer, Susanne König, Lutz König, Rie Nishio, and Anja Regen. 2018. Public dgs corpus: Annotation conventions. Technical report, Project Note AP03-2018-01, DGS-Korpus project, IDGS, Hamburg University. find
  47. Alfarabi Imashev, Medet Mukushev, Vadim Kimmelman, and Anara Sandygulova. 2020. A dataset for linguistic understanding, visual evaluation, and recognition of sign languages: The k-rsl. In Proceedings of the 24th Conference on Computational Natural Language Learning, pages 631–640. find
  48. Annelies Kusters, Maartje De Meulder, and Dai O’Brien. 2017. Innovations in deaf studies: The role of deaf scholars. Oxford University Press. find
  49. Amy Isard. 2020. Approaches to the anonymisation of sign language corpora. In Proceedings of the LREC2020 9th Workshop on the Representation and Processing of Sign Languages: Sign Language Resources in the Service of the Language Community, Technological Challenges and Application Perspectives, page… find
  50. David L Jaffe. 1994. Evolution of mechanical fingerspelling hands for people who are deaf-blind. Journal of rehabilitation research and development, 31(3):236–244. find
  51. Robert E Johnson and Scott K Liddell. 2011. Toward a phonetic representation of signs: Sequentiality and contrast. Sign Language Studies, 11(2):241–274. find
  52. Trevor Johnston. 2010. From archive to corpus: Transcription and annotation in the creation of signed language corpora. International journal of corpus linguistics, 15(1):106–131. find
  53. Trevor Johnston and Louise De Beuzeville. 2016. Auslan corpus annotation guidelines. Auslan Corpus. find
  54. Trevor Johnston and Adam Schembri. 2007. Australian Sign Language (Auslan): An introduction to sign language linguistics. Cambridge University Press. find
  55. Trevor Johnston and Adam C Schembri. 1999. On defining lexeme in a signed language. Sign language & linguistics, 2(2):115–185. find
  56. Jim Kakumasu. 1968. Urubu sign language. International journal of American linguistics, 34(4):275– 281. find
  57. Vadim Kimmelman. 2014. Information structure in russian sign language and sign language of the netherlands. find
  58. Sang-Ki Ko, Chang Jo Kim, Hyedong Jung, and Choongsang Cho. 2019. Neural sign language translation based on human keypoint estimation. Applied Sciences, 9(13):2683. find
  59. Oscar Koller. 2020. Quantitative survey of the state of the art in sign language recognition. arXiv preprint arXiv:2008.09918. — [arXiv:2008.09918](https://arxiv.org/abs/2008.09918) find
  60. Dongxu Li, Cristian Rodriguez, Xin Yu, and Hongdong Li. 2020. Word-level deep sign language recognition from video: A new large-scale dataset and methods comparison. In The IEEE Winter Conference on Applications of Computer Vision, pages 1459–1469. find
  61. Scott K Liddell and Robert E Johnson. 1989. American sign language: The phonological base. Sign language studies, 64(1):195–277. find
  62. Scott K Liddell and Melanie Metzger. 1998. Gesture in sign language discourse. Journal of pragmatics, 30(6):657–697. find
  63. Scott K Liddell et al. 2003. Grammar, gesture, and meaning in American Sign Language. Cambridge University Press. find
  64. David McKee and Graeme Kennedy. 2000. Lexical comparison of signs from american, australian, british and new zealand sign languages. The signs of language revisited: An anthology to honor Ursula Bellugi and Edward Klima, pages 49–76. find
  65. Johanna Mesch and Lars Wallin. 2012. From meaning to signs and back: Lexicography and the swedish sign language corpus. In Proceedings of the 5th Workshop on the Representation and Processing of Sign Languages: Interactions between Corpus and Lexicon [Language Resources and Evaluation Conference (LR… find
  66. Johanna Mesch and Lars Wallin. 2015. Gloss annotations in the swedish sign language corpus. International Journal of Corpus Linguistics, 20(1):102– 120. find
  67. Caio DD Monteiro, Christy Maria Mathew, Ricardo Gutierrez-Osuna, and Frank Shipman. 2016. Detecting and identifying sign languages through visual features. In 2016 IEEE International Symposium on Multimedia (ISM), pages 287–290. IEEE. find
  68. Kathryn Montemurro and Diane Brentari. 2018. Emphatic fingerspelling as code-mixing in american sign language. Proceedings of the Linguistic Society of America, 3(1):61–1. find
  69. Amit Moryossef, Ioannis Tsochantaridis, Roee Aharoni, Sarah Ebling, and Srini Narayanan. 2020. Real-time sign language detection using human pose estimation. In European Conference on Computer Vision, pages 237–248. Springer. find
  70. Amit Moryossef, Kayo Yin, Graham Neubig, and Yoav Goldberg. 2021. Data augmentation for sign language gloss translation. arXiv preprint arXiv:2105.07476. find
  71. Joseph J Murray, Wyatte C Hall, and Kristin Snoddon. 2020. The importance of signed languages for deaf children and their families. The Hearing Journal, 73(3):30–32. find
  72. Sylvie CW Ong and Surendra Ranganath. 2005. Automatic sign language analysis: A survey and the future beyond lexical meaning. IEEE Computer Architecture Letters, 27(06):873–891. find
  73. Ellen Ormel and Onno Crasborn. 2012. Prosodic correlates of sentences in signed languages: A literature review and suggestions for new types of studies. Sign Language Studies, 12(2):279–315. find
  74. C. Padden. 1988. Interaction of Morphology and Syntax in American Sign Language. Outstanding Disc Linguistics Series. Garland. find
  75. Carol A Padden. 1998. The asl lexicon. Sign language & linguistics, 1(1):39–60. find
  76. Carol A Padden and Tom Humphries. 1988. Deaf in America. Harvard University Press. find
  77. Becky Sue Parton. 2006. Sign language recognition and translation: A multidisciplined approach from the field of artificial intelligence. Journal of deaf studies and deaf education, 11(1):94–101. find
  78. Carol J Patrie and Robert E Johnson. 2011. Fingerspelled word recognition through rapid serial visual presentation: RSVP. DawnSignPress. find
  79. Leonid Pishchulin, Arjun Jain, Mykhaylo Andriluka, Thorsten Thorm ä hlen, and Bernt Schiele. 2012. Articulated people detection and pose estimation: Reshaping the future. In 2012 IEEE Conference on Computer Vision and Pattern Recognition, pages 3178–3185. IEEE. find
  80. Vineel Pratap, Qiantong Xu, Anuroop Sriram, Gabriel Synnaeve, and Ronan Collobert. 2020. MLS: A Large-Scale Multilingual Dataset for Speech Research. In Proc. our card
  81. Interspeech 2020, pages 2757– 2761. find
  82. Siegmund Prillwitz and Heiko Zienert. 1990. Hamburg notation system for sign language: Development of a sign writing with computer application. In Current trends in European Sign Language Research. Proceedings of the 3rd European Congress on Sign Language Research, pages 355–379. find
  83. Javier Ramırez, José C Segura, Carmen Benıtez, Angel De La Torre, and Antonio Rubio. 2004. Efficient voice activity detection algorithms using long-term speech information. Speech communication, 42(3-4):271–287. find
  84. Razieh Rastgoo, Kourosh Kiani, and Sergio Escalera. 2020. Sign language recognition: A deep survey. Expert Systems with Applications, page 113794. find
  85. Christian Rathmann and Gaurav Mathur. 2011. A featural approach to verb agreement in signed languages. Theoretical Linguistics, 37(3-4):197–208. find
  86. Cynthia B Roy. 2011. Discourse in signed languages. Gallaudet University Press. find
  87. Wendy Sandler. 2010. Prosody and syntax in sign languages. Transactions of the philological society, 108(3):298–328. find
  88. Wendy Sandler. 2012. The phonological organization of sign languages. Language and linguistics compass, 6(3):162–182. find
  89. Pinar Santemiz, Oya Aran, Murat Saraclar, and Lale Akarun. 2009. Automatic sign segmentation from continuous signing via multiple sequence alignment. In 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops, pages 2001–2008. IEEE. find
  90. Ben Saunders, Necati Cihan Camgöz, and Richard Bowden. 2020a. Everybody sign now: Translating spoken language to photo realistic sign language video. arXiv preprint arXiv:2011.09846. — [arXiv:2011.09846](https://arxiv.org/abs/2011.09846) find
  91. Ben Saunders, Necati Cihan Camgöz, and Richard Bowden. 2020b. Progressive transformers for end-to-end sign language production. In European Conference on Computer Vision, pages 687–705. find
  92. Adam Schembri, Kearsy Cormier, and Jordan Fenlon. 2018. Indicating verbs as typologically unique constructions: Reconsidering verb ‘agreement’in sign languages. Glossa: a journal of general linguistics, 3(1). find
  93. B. Shi, A. Martinez Del Rio, J. Keane, D. Brentari, G. Shakhnarovich, and K. Livescu. 2019. Fingerspelling recognition in the wild with iterative visual attention. ICCV. find
  94. B. Shi, A. Martinez Del Rio, J. Keane, J. Michaux, G. Shakhnarovich D. Brentari, and K. Livescu. 2018. American sign language fingerspelling recognition in the wild. SLT. find
  95. Edgar H Shroyer and Susan P Shroyer. 1984. Signs across America: A look at regional differences in American Sign Language. Gallaudet University Press. find
  96. Ozge Mercanoglu Sincan and Hacer Yalim Keles. 2020. Autsl: A large scale multi-modal turkish sign language dataset and baseline methods. IEEE Access, 8:181340–181355. find
  97. Jongseo Sohn, Nam Soo Kim, and Wonyong Sung. 1999. A statistical model-based voice activity detection. IEEE signal processing letters, 6(1):1–3. find
  98. Markus Steinbach and Edgar Onea. 2016. A DRT analysis of discourse referents and anaphora resolution in sign language. Journal of Semantics, 33(3):409– 448. find
  99. Jr. Stokoe, William C. 1960. Sign Language Structure: An Outline of the Visual Communication Systems of the American Deaf. The Journal of Deaf Studies and Deaf Education, 10(1):3–37. find
  100. Spain (Online). International Committee on Computational Linguistics. find
  101. Jan Zelinka and Jakub Kanis. 2020. Neural sign language synthesis: Words are our glosses. In The IEEE Winter Conference on Applications of Computer Vision, pages 3395–3403. find
  102. William C Stokoe Jr. 2005. Sign language structure: An outline of the visual communication systems of the american deaf. Journal of deaf studies and deaf education, 10(1):3–37. find
  103. Stephanie Stoll, Necati Cihan Camgöz, Simon Hadfield, and Richard Bowden. 2018. Sign language production using neural machine translation and generative adversarial networks. In Proceedings of the 29th British Machine Vision Conference (BMVC 2018). British Machine Vision Association. find
  104. Stephanie Stoll, Necati Cihan Camgöz, Simon Hadfield, and Richard Bowden. 2020. Text2sign: towards sign language production using neural machine translation and generative adversarial networks. International Journal of Computer Vision, pages 1–18. find
  105. Ted Supalla. 1986. The classifier system in american sign language. Noun classes and categorization, 7:181–214. find
  106. Valerie Sutton. 1990. Lessons in sign writing. Sign-Writing. find
  107. Hamid Vaezi Joze and Oscar Koller. 2019. Ms-asl: A large-scale data set and benchmark for understanding american sign language. In The British Machine Vision Conference (BMVC). find
  108. Sherman Wilcox. 1992. The phonetics of fingerspelling, volume 4. John Benjamins Publishing. find
  109. Sherman Wilcox and Sarah Hafer. 2004. Rethinking classifiers. emmorey, k.(ed.).(2003). perspectives on classifier constructions in sign languages. mahwah, nj: Lawrence erlbaum associates. 332 pages. hardcover. find
  110. Qinkun Xiao, Minying Qin, and Yuting Yin. 2020. Skeleton-based chinese sign language recognition and generation for bidirectional communication between deaf and hearing people. Neural Networks, 125:41–55. find
  111. Kayo Yin and Jesse Read. 2020a. Attention is all you sign: sign language translation with transformers. In Sign Language Recognition, Translation and Production (SLRTP) Workshop-Extended Abstracts, volume 4. find
  112. Kayo Yin and Jesse Read. 2020b. Better sign language translation with STMC-transformer. In Proceedings of the 28th International Conference on Computational Linguistics, pages 5975–5989, Barcelona, find

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