skip to main content
research-article

State of the Art of Automation in Sign Language: A Systematic Review

Published:06 April 2023Publication History
Skip Abstract Section

Abstract

Sign language is the fundamental communication language of deaf people. Efforts to develop sign language generation systems can make the life of these people smooth and effortless. Despite the importance of sign language generation systems, there is a paucity of a systematic literature review. This is the foremost recognizable scholastic literature review of sign language generation systems. It presents a scholastic database of the literature between 1998 and 2020 and suggests classification criteria to systematize research studies. Four hundred fourteen research studies were recognized and reviewed for their direct pertinence to sign language generation systems. One hundred sixty-two research studies were subsequently chosen, examined, and classified. Each of the 162 chosen research papers was categorized based on 30 sign languages and was further comparatively analyzed based on seven comparison parameters (input form, translation technologies, application domain, use of parsers/grammars, manual/non-manual features, accuracy, and output form). It is evident from our research findings that the majority of research on sign language generation was carried out using data-driven approaches in the absence of proper grammar rules and generated only manual signs. This research study may provide researchers a roadmap toward future research directions and facilitate the compilation of information in the field of sign language generation.

REFERENCES

  1. [1] Anuja K., Suryapriya S., and Idicula S. M.. 2009. Design and development of a frame based MT system for English-to-ISL. In Proceedings of the World Congress on Nature and Biologically Inspired Computing (NABIC’09), 1382–1387. Google ScholarGoogle ScholarCross RefCross Ref
  2. [2] Zeshan U.. 2003. Indo-Pakistani Sign Language grammar: A typological outline. Sign Lang. Stud. 3, 2 (2003), 157212.Google ScholarGoogle ScholarCross RefCross Ref
  3. [3] World Health Organization. 2022. Retrieved March 1, 2022 from https://www.who.int/en/news-room/fact-sheets/detail/deafness-and-hearing-loss.Google ScholarGoogle Scholar
  4. [4] National Center for Health Statistics. 2022. Retrieved March 1, 2022 from https://www.startasl.com/american-sign-language.Google ScholarGoogle Scholar
  5. [5] BDA: British Deaf Association, BSL Statistics. 2022. Retrieved March 1, 2022 from https://bda.org.uk/help-resources/#statistics.Google ScholarGoogle Scholar
  6. [6] European center for Modern Languages. 2022. Retrieved March 1, 2022 from https://edl.ecml.at/Facts/FAQsonsignlanguage/tabid/2741/language/Default.aspx.Google ScholarGoogle Scholar
  7. [7] Robotka Z.. 2022. Signall. Retrieved March 2022 from http://www.signall.us.Google ScholarGoogle Scholar
  8. [8] Elwazer M.. 2022. Kintrans. Retrieved March 1, 2022 from http://www.kintrans.com.Google ScholarGoogle Scholar
  9. [9] Dasgupta T., Dandpat S., and Basu A.. 2008a. Prototype machine translation system from text-to-Indian Sign Language. In Proceedings of the International Conference on Intelligent User Interfaces, 313316. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. [10] Kitchenham B., Brereton O. P., Budgen D., Turner M., Bailey J., and Linkman S.. 2009. Systematic literature reviews in software engineering—A systematic literature review. Inf. Softw. Technol. 51, 1 (2009), 715.Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. [11] Eberhard David M., Simons Gary F., and Fennig Charles D. (eds.). 2021. Ethnologue: Languages of the World. (24th ed.). SIL International. Dallas, Texas.Google ScholarGoogle Scholar
  12. [12] Goyal L. and Goyal V.. 2016. Text to sign language translation system. Int. J. Synth. Emot. 7, 2 (2016), 6277. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. [13] Ayadi K., Elhadj Y. O. M., and Ferchichi A.. 2018. Automatic translation from Arabic to Arabic sign language: A review. In Proceedings of the JCCO Joint International Conference on ICT in Education and Training, International Conference on Computing in Arabic, and International Conference on Geocomputing (JCCO: TICET-ICCA-GECO’18), 1115. Google ScholarGoogle ScholarCross RefCross Ref
  14. [14] Chikalthankar S. and Ghotkar A.. 2020. Sign language generation—A survey of techniques. Int. J. Innov. Technol. Explor. Eng. 9, 9 (2020), 473476. Google ScholarGoogle ScholarCross RefCross Ref
  15. [15] Veale T., Conway A., and Collins B.. 1998. The challenges of cross-modal translation: English-to-sign-language translation in the Zardoz system. Mach. Transl. 13 (1998), 81106. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. [16] Grieve-Smith A. B.. 1999. English to American Sign Language machine translation of weather reports. In Proceedings of the 2nd High Desert Student Conference in Linguistics (HDSL2’99), 4655.Google ScholarGoogle Scholar
  17. [17] Zhao L., Kipper K., Schuler W., Vogler C., Badler N., and Palmer M.. 2000. A machine translation system from English to American Sign Language. In Proceedings of the Conference of the Association for Machine Translation in the Americas. Springer, Berlin, 5467.Google ScholarGoogle ScholarCross RefCross Ref
  18. [18] Speers d'A.. 2001. Representation of ASL for Machine Translation. Ph.D. Dissertation, Georgetown University.Google ScholarGoogle Scholar
  19. [19] Grieve-Smith A. B.. 2002. SignSynth: A sign language synthesis application using Web3D and perl. In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 2298, 134145. Google ScholarGoogle ScholarCross RefCross Ref
  20. [20] Scarlatos T., Scarlatos L., and Gallarotti F.. 2003. iSign: Making the benefits of reading aloud accessible to families with deaf children. In Proceedings of the IASTED International Conference on Computer Graphics and Imaging. 7478.Google ScholarGoogle Scholar
  21. [21] Papadogiorgaki M. and Grammalidis N.. 2004. VSigns—A virtual sign synthesis web tool. In Conference: Proc. 6th COST 276 Workshop on Information and Knowledge Management for Integrated Media Communication. https://www.researchgate.net/publication/230608781_VSigns_-_A_Virtual_Sign_Synthesis_Web_Tool.Google ScholarGoogle Scholar
  22. [22] Papadogiorgaki M., Grammalidis N., Tzovaras D., and Strintzis M. G.. 2005. Text-to-sign language synthesis tool. In Proceedings of the 13th European Signal Processing Conference (EUSIPCO’05), 25212524.Google ScholarGoogle Scholar
  23. [23] Huenerfauth M.. 2004. A Multi-path Architecture for Machine Translation of English Text into American Sign Language Animation, 2530. Google ScholarGoogle ScholarCross RefCross Ref
  24. [24] Huenerfauth M.. 2005. American sign language generation: Multimodal NLG with multiple linguistic channels. In Proceedings of the Conference 43rd Annual Meeting of the Association for Computational Linguistics (ACL’05), 3742. Google ScholarGoogle ScholarCross RefCross Ref
  25. [25] Huenerfauth M.. 2006. Generating American Sign Language Classifier Predicates for English-to-ASL Machine Translation. Ph.D. Dissertation, University of Pennsylvania.Google ScholarGoogle Scholar
  26. [26] Huenerfauth M., Zhao L., Gu E., and Allbeck J.. 2007. Design and evaluation of an American Sign Language generator. In Proceedings of the Workshop on Embodied Language Processing, Association for Computational Linguistics, Prague, 51--58. https://aclanthology.org/W07-1907/.Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. [27] Othman A. and Jemni M.. 2011. Statistical sign language machine translation: From English written text to American Sign Language gloss IJCSI International Journal of Computer Science Issues 8, 5 (2011), 65--73. Google ScholarGoogle ScholarCross RefCross Ref
  28. [28] Othman A. and Jemni M.. 2012. English-ASL Gloss Parallel Corpus 2012: ASLG-PC12. In Conference: 5th Workshop on the Representation and Processing of Sign Languages LREC12.Google ScholarGoogle Scholar
  29. [29] Bonham M. E., Elizabeth M., and Bonham J.. 2015. English to ASL Gloss Machine Translation. Ph.D. Dissertation, Brigham Young University.Google ScholarGoogle Scholar
  30. [30] Manzano D. M.. 2018. English to ASL Translator for SPEECH2SIGNS. Retrieved March 16, 2021 from https://www.semanticscholar.org/paper/english-to-asl-translator-for-speech2signs-Manzano/88d6a9573b9a2d0cf54c90e947f4fbe12578fbca.Google ScholarGoogle Scholar
  31. [31] Mohandes M.. 2006. Automatic translation of Arabic text to Arabic Sign Language. AIML J. 6, 4 (2006), 1519.Google ScholarGoogle Scholar
  32. [32] Halawani S.. 2008. Arabic sign language translation system on mobile devices. Int.l J. Comput. Sci. Netw. Secur. 8, 1 (2008), 251256.Google ScholarGoogle Scholar
  33. [33] Almasoud A. M. and Al-Khalifa H. S.. 2011. A proposed semantic machine translation system for translating Arabic text to Arabic Sign Language. In Proceedings of the 2nd Kuwait Conference on E-Services and e-Systems (KCESS’11). Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. [34] Almasoud A. M. and Al-Khalifa H. S.. 2012. SemSignWriting: A proposed semantic system for Arabic text-to-signwriting translation. J. Softw. Eng. Appl. 5, 8 (2012), 604612. Google ScholarGoogle ScholarCross RefCross Ref
  35. [35] Almohimeed Abdulaziz, Wald M., and Damper R. I.. 2011. Arabic text to Arabic Sign Language translation system for the deaf and hearing-impaired community. In Proceedings of the 2nd Workshop on Speech and Language Processing for Assistive Technologies (SLPAT’11), 101109.Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. [36] Al Ameiri F., Zemerly M. J., and Al Marzouqi M.. 2011. Mobile Arabic Sign Language. In Proceedings of the International Conference for Internet Technology and Secured Transactions (ICITST’11), 363367.Google ScholarGoogle Scholar
  37. [37] Halawani S. M., Daman D., Kari S., and Ahmad A. R.. 2013. An avatar based translation system from Arabic speech to Arabic Sign Language for deaf people. Int. J. Comput. Sci. Netw. Secur. 13, 12 (2013), 4352.Google ScholarGoogle Scholar
  38. [38] Aouiti N.. 2013. Towards an automatic translation from Arabic text to sign language. In Proceedings of the 4th International Conference on Information and Communication Technology and Accessibility (ICTA’13). Google ScholarGoogle ScholarCross RefCross Ref
  39. [39] Aouiti N. and Jemni M.. 2018. Translation system from Arabic text to Arabic Sign Language. J. Appl. Intell. Syst. 3, 2 (2018), 5770. Google ScholarGoogle ScholarCross RefCross Ref
  40. [40] Aouiti N., Jemni M., and Semreen S.. 2017. Arab gloss and implementation for Arabic Sign Language. In Proceedings of the 6th International Conference on Information and Communication Technology and Accessbility (ICTA’17), 16. Google ScholarGoogle ScholarCross RefCross Ref
  41. [41] El A. E. E. Alfi and EL S. M. Atawy. 2018. Intelligent Arabic Sign Language to Arabic text Translation for easy deaf communication. International Journal of Computer Applications 180, 41 (2018), 19--26. https://www.ijcaonline.org/archives/volume180/number41/29403-2018917081.Google ScholarGoogle Scholar
  42. [42] El-Gayyar M. M., Ibrahim A. S., and Wahed M. E.. 2016. Translation from Arabic speech to Arabic Sign Language based on cloud computing. Egypt. Inf. J. 17, 3 (2016), 295303. Google ScholarGoogle ScholarCross RefCross Ref
  43. [43] Al-Barahamtoshy O. H. and Al-Barhamtoshy H. M.. 2017. Arabic text-to-sign (ArTTS) model from automatic SR system. Proc. Comput. Sci. 117 (2017), 304311. Google ScholarGoogle ScholarCross RefCross Ref
  44. [44] Luqman H. and Mahmoud S. A.. 2018. Automatic translation of Arabic text-to-Arabic Sign Language. Univ. Access Inf. Soc. 18, 4 (2018), 939951. Google ScholarGoogle ScholarCross RefCross Ref
  45. [45] Ayadi K., Elhadj Y. O. M., and Ferchichi A.. 2018. Prototype for learning and teaching Arabic Sign Language using 3D animations. In Proceedings of the International Conference on Intelligent Autonomous Systems (ICoIAS’18), 5157. Google ScholarGoogle ScholarCross RefCross Ref
  46. [46] Brour M. and Benabbou A.. 2019. ATLASLang MTS 1: Arabic text language into Arabic Sign Language machine translation system. Proc. Comput. Sci. 148 (2019) 236245. Google ScholarGoogle ScholarDigital LibraryDigital Library
  47. [47] H. M. Al-Barhamtoshy, N. E. Abuzinadah, A. Nabawi, T. F. Himdi, A. A. Malibari, and A. A. Allinjawi. 2019. Development of an intelligent Arabic text translation model for deaf students using state of the art information technology. Biosci. Biotechnol. Res. Commun. 12, 2 (2019), 338345. 7Google ScholarGoogle ScholarCross RefCross Ref
  48. [48] El Anigri S., Himmi M. Majid, and Mahmoudi A.. 2005. Towards a sign language gloss representation of modern standard Arabic. ArXiv, 1--4. Google ScholarGoogle ScholarCross RefCross Ref
  49. [49] Bangham J. A., Cox S. J., Elliott R., Glauert J. R. W., Marshall I., Rankov S., and Wells M.. 2000. Virtual signing: Capture, animation, storage and transmission—An overview of the ViSiCAST project. IEE Colloq. 25 (2000), 2329. Google ScholarGoogle ScholarCross RefCross Ref
  50. [50] Safar E. and Marshall I.. 2001. Translation of English text to a DRS-based sign language oriented semantic representation. In Proceedings of the Conference on Automatic Treatment Natural Languages (TALN’01), 297306.Google ScholarGoogle Scholar
  51. [51] Sáfár É. and Marshall I.. 2002a. Sign language translation via DRT and HPSG. In Proceedings of the Conference on Computational Linguistics and Intelligent Text Processing. (CICLing’02), Lecture Notes in Computer Science, Vol. 2276, A. Gelbukh (ed.). Springer, Berlin. Google ScholarGoogle ScholarCross RefCross Ref
  52. [52] Marshall I. and Sáfár É.. 2002b. Sign language generation using HPSG. Inf. Syst. (2002), 110Google ScholarGoogle Scholar
  53. [53] Kennaway R.. 2002. Synthetic animation of deaf signing gestures. In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 2298, 146157. Google ScholarGoogle ScholarCross RefCross Ref
  54. [54] Marshall I. and Sáfár É.. 2003. Computer Science, Linguistics. Google ScholarGoogle ScholarDigital LibraryDigital Library
  55. [55] Cox S., Lincoln M., Tryggvason J., Nakisa M., Wells M., Tutt M., and Abbott S.. 2002. TESSA, a system to aid communication with deaf people. In Proceedings of the Annual ACM Conference on Assistive Technologies, 205212. Google ScholarGoogle ScholarCross RefCross Ref
  56. [56] Cox S., Lincoln M., Tryggvason J., Nakisa M., Wells M., Tutt M., and Abbott S.. 2003. The development and evaluation of a speech-to-sign translation system to assist transactions. Int. J. Hum.–Comput. Interact. 16, 2 (2003), 141161. Google ScholarGoogle ScholarCross RefCross Ref
  57. [57] Wray A., Cox S., Lincoln M., and Tryggvason J.. 2004. A formulaic approach to translation at the post office: Reading the signs. Lang. Commun. 24, 1 (2004), 5975. Google ScholarGoogle ScholarCross RefCross Ref
  58. [58] Glauert J. R. W., Elliott R., Cox S. J., and Sheard M.. 2006. VANESSA—A system for communication between deaf and hearing people. Technol. Disabil. 18, 4 (2006), 207216. Google ScholarGoogle ScholarCross RefCross Ref
  59. [59] Elliott R., Glauert J. R. W., Kennaway J. R., Marshall I., and Safar E.. 2008. Linguistic modelling and language-processing technologies for Avatar-based sign language presentation. Univ, Access Inf. Soc. 6, 4 (2008), 375391. Google ScholarGoogle ScholarDigital LibraryDigital Library
  60. [60] Kar P., Reddy M., Mukerjee A., and Raina A. M.. 2007. INGIT: Limited domain formulaic translation from Hindi strings to Indian Sign Language. InProceedings of the International Conference on Natural Language Processing (ICON’14).Google ScholarGoogle Scholar
  61. [61] Dasgupta T. and Basu A.. 2008b. An English to Indian Sign Language machine translation system. Retrieved March 16, 2021 from http://www.cse.iitd.ac.in/∼assistech/Proceedings/P17.pdf.Google ScholarGoogle Scholar
  62. [62] Ali S. F., Mishra G. S., and Sahoo A. K.. 2013. Domain bounded English to Indian Sign Language translation model. Int. J. Comput. Sci. Inf. 3, 1 (2013), 4145.Google ScholarGoogle Scholar
  63. [63] Ali S. F.. 2013. Issues in English to Indian sign generation and translation model and developed corpus based translation system to tackle those issues. In Proceedings of the ICEECMPE International Conference. 5359.Google ScholarGoogle Scholar
  64. [64] Raghavan R. J., Prasad K. A., Muraleedharan R., and Geetha M.. 2013. Animation system for indian sign language communication using LOTS notation. In Proceedings of the International Conference on Emerging Trends in Communication, Control, Signal Processing and Computing Applications (IEEE-C2SPCA’13). Google ScholarGoogle ScholarCross RefCross Ref
  65. [65] Kaur R. and Kumar P.. 2014. HamNoSys generation system for sign language. In Proceedings of the International Conference on Advances in Computing, Communications and Informatics (ICACCI’14), 27272734. Google ScholarGoogle ScholarCross RefCross Ref
  66. [66] Kaur R.. 2014. Sign Language Automation. Master's Dissertation, Thapar University, Punjab, India.Google ScholarGoogle Scholar
  67. [67] Joy J. and Balakrishnan K.. 2014. A prototype Malayalam to Sign Language automatic translator. arXiv:1412.7415. Retrieved from http://arxiv.org/abs/1412.7415.Google ScholarGoogle Scholar
  68. [68] Kaur S. and Singh M.. 2015. Indian Sign Language animation generation system. In Proceedings of the 1st International Conference on Next Generation Computing Technologies (NGCT’15), 909914. Google ScholarGoogle ScholarCross RefCross Ref
  69. [69] Verma A. and Kaur S.. 2015. Indian Sign Language animation generation system for Gurumukhi script. Int. J. Comput. Sci. Technol. 6, 3 (2015), 117121.Google ScholarGoogle Scholar
  70. [70] Nair M. S., Nimitha A. P., and Idicula S. M.. 2016. Conversion of Malayalam text to Indian Sign Language using synthetic animation. In Proceedings of the International Conference on Next Generation Intelligent Systems (ICNGIS’16), 14. Google ScholarGoogle ScholarCross RefCross Ref
  71. [71] Goyal L. and Goyal V.. 2016a. Automatic translation of English text to Indian Sign Language synthetic animations. In Proceedings of the 13th International Conference on Natural Language Processing. 144153Google ScholarGoogle Scholar
  72. [72] Goyal L. and Goyal V.. 2016b. Development of Indian Sign Language dictionary using synthetic animations. Ind. J. Sci. Technol. 9, 32 (2016). Google ScholarGoogle ScholarCross RefCross Ref
  73. [73] Vij P. and Kumar P.. 2016. Mapping Hindi text to Indian Sign Language with extension using wordnet. In Proceedings of the ACM International Conference on Advances in Information Communication Technology & Computing. 15. Google ScholarGoogle ScholarDigital LibraryDigital Library
  74. [74] Goyal L. and Goyal V.. 2017. Tutorial for deaf—Teaching Punjabi alphabet using synthetic animations. In Proceedings of the 14th International Conference on Natural Language Processing. 172--177.Google ScholarGoogle Scholar
  75. [75] Mishra G. S., Sahoo A. K., and Ravulakollu K. K.. 2017. Word based statistical machine translation from English text to Indian Sign Language. ARPN J. Eng. Appl. Sci. 12, 2 (2017), 481488.Google ScholarGoogle Scholar
  76. [76] Varghese M. and Nambiar S. K.. 2018. English to SiGML conversion for sign language generation. In Proceedings of the International Conference on Circuits and Systems in Digital Enterprise Technology (ICCSDET’18), 16. Google ScholarGoogle ScholarCross RefCross Ref
  77. [77] Goyal L. and Goyal V.. 2019. Tutorial for deaf—Teaching Hindi alphabet using synthetic animations. Gyancity J. Eng. Technol. 5, 1 (2019), 2633. Google ScholarGoogle ScholarCross RefCross Ref
  78. [78] Mishra G. S. and Asteya P.. 2019a. Generating glosses of Indian Sign Language from English texts: A proposed hybrid machine translation method. International Journal of Innovations in Engineering and Technology (IJIET) 13, 1 (2019), 120125.Google ScholarGoogle Scholar
  79. [79] Mishra G. S., Nand P., and Pooja. 2019b. English text to Indian Sign Language machine translation: A rule based method. Int. J. Innov. Technol. Explor. Eng. 8, 10 (2019), 460467. Google ScholarGoogle ScholarCross RefCross Ref
  80. [80] Goyal D., Goyal V., and Goyal L.. 2020. Rule based translation of English complex/compound sentences into Indian Sign Language synthetic video animations. Alochana Chakra J. 9, 9 (2020), 339348.Google ScholarGoogle Scholar
  81. [81] Dhanjal A. and Singh W.. 2020. An automatic conversion of Punjabi text to Indian Sign Language. ICST Trans. Scal. Inf. Syst. (2020), 165279. Google ScholarGoogle ScholarCross RefCross Ref
  82. [82] Patel B. D., Patel H. B., Khanvilkar M. A., Patel N. R., and Akilan T.. 2020. ES2ISL: An advancement in speech to sign language translation using 3d avatar animator. In Proceedings of the Canadian Conference on Electrical and Computer Engineering. Google ScholarGoogle ScholarCross RefCross Ref
  83. [83] San-Segundo R., Montero J. M., Macías-Guarasa J., Córdoba R., Ferreiros J., and Pardo J. M.. 2004. Generating gestures from speech. In Proceedings of the 8th International Conference on Spoken Language Processing (ICSLP’04), 18171820.Google ScholarGoogle ScholarCross RefCross Ref
  84. [84] Tejedor J., López F., Bolaños D., and Colás J.. 2006. Augmented Service for Deaf People Using a Text to Sign Language Translator. https://www.academia.edu/16702795/Augmented_Service_for_Deaf_People_Using_a_Text_to_Sign_Language_Translator.Google ScholarGoogle Scholar
  85. [85] San-Segundo R., Barra R., D'haro L. F., Montero J. M., Córdoba R., and Ferreiros J.. 2006. A Spanish speech to sign language translation system for assisting deaf-mute people. In Proceedings of the Annual Conference of the International Speech Communication Association and the 9th International Conference on Spoken Language Processing (INTERSPEECH-ICSLP’06), 13991402.Google ScholarGoogle ScholarCross RefCross Ref
  86. [86] San-Segundo R., Barra R., Córdoba R.., D'Haro L. F., Fernández F., Ferreiros J., Lucas J. M., Macías-Guarasa J., Montero J. M., and Pardo J. M.. 2008. Speech to sign language translation system for Spanish. Speech Commun. 50, 1112 (2008), 10091020. Google ScholarGoogle ScholarDigital LibraryDigital Library
  87. [87] Baldassarri S., Cerezo E., and Royo-Santas F.. 2009. Automatic translation system to Spanish sign language with a virtual interpreter. In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 5726, 196199. Google ScholarGoogle ScholarDigital LibraryDigital Library
  88. [88] San-Segundo R., Montero J. M., Córdoba R., Sama V., Fernández F., D'Haro L. F., López-Ludeña V., Sánchez D., and García A.. 2012. Design, development and field evaluation of a Spanish into sign language translation system. Pattern Anal. Appl. 15, 2 (2012), 203224. Google ScholarGoogle ScholarCross RefCross Ref
  89. [89] Verónica López-Ludeña, San-Segundo R., Montero J. M., Córdoba R., Ferreiros J., and Pardo J. M.. 2012. Automatic categorization for improving Spanish into Spanish Sign Language machine translation. Comput. Speech Lang. 26, 3 (2012), 149167. Google ScholarGoogle ScholarDigital LibraryDigital Library
  90. [90] Verónica López-Ludeña, San-Segundo R., González Morcillo C., López J. C., and Pardo Muñoz J. M.. 2013. Increasing adaptability of a speech into sign language translation system. Expert Syst. Appl. 40, 4 (2013), 13121322. Google ScholarGoogle ScholarDigital LibraryDigital Library
  91. [91] López-Ludeña V., González-Morcillo C., López J. C., Barra-Chicote R., Cordoba R., and San-Segundo R.. 2014. Translating bus information into sign language for deaf people. Eng. Appl. Artif. Intell. 32 (2014), 258269. Google ScholarGoogle ScholarCross RefCross Ref
  92. [92] Porta J., López-Colino F., Tejedor J., and Colás J.. 2014. A rule-based translation from written Spanish to Spanish sign language glosses. Comput. Speech Lang. 28, 3 (2014), 788811. Google ScholarGoogle ScholarDigital LibraryDigital Library
  93. [93] Eshaque A., Hamid T., Rahman S., and Rokonuzzaman M.. 2002. A novel concept of 3d animation based “intelligent assistant” for deaf people: For understanding Bengali expressions. International Conference on Computer and Information Technology (ICCIT'02).Google ScholarGoogle Scholar
  94. [94] Sarkar B., Datta K., Datta C. D., Sarkar D., Dutta S. J., Das. Roy I., Paul A., Molla J. U., and Paul A.. 2009. A Translator for Bangla Text to Sign Language. 36.Google ScholarGoogle Scholar
  95. [95] Hoque T. and Kabir F.. 2016. Automated Bangla sign language translation system: Prospects. Limit. Appl. (2016), 856862.Google ScholarGoogle Scholar
  96. [96] Shahriar R., Zaman A. G. M., Ahmed T., Khan S. M., and Maruf H. M.. 2017. A communication platform between Bangla and sign language. In Proceedings of the 5th IEEE Region 10 Humanitarian Technology Conference (R10-HTC’17), 14.Google ScholarGoogle ScholarCross RefCross Ref
  97. [97] Xu L. and Gao W.. 2000. Study on translating Chinese into Chinese Sign Language. J. Comput. Sci. Technol. 15, 5 (2000), 485490. Google ScholarGoogle ScholarDigital LibraryDigital Library
  98. [98] Xu X., Wang X., Yao L., Zhang D., and Zhao H.. 2008. Avatars based Chinese sign language synthesis system. In Proceedings of the IEEE International Conference on Systems, Man and Cybernetics. 444449. Google ScholarGoogle ScholarCross RefCross Ref
  99. [99] Wang J., Sun Y., and Wang L.. 2010. Chinese Sign Language animation system on mobile devices. In Proceedings of the 2nd International Conference on Information Technology and Computer Science (ITCS’10), 5255. Google ScholarGoogle ScholarDigital LibraryDigital Library
  100. [100] Song D., Wang X., and Xu X.. 2012. Chinese Sign Language synthesis system on mobile device. Proc. Eng. 29 (2012), 986992. Google ScholarGoogle ScholarCross RefCross Ref
  101. [101] Jemni M. and Elghoul O.. 2007. Towards web-based automatic interpretation of written text to sign language. In Proceedings of the IEEE International Conference on Integrated Circuits, Technologies and Applications (ICTA’07). 4348.Google ScholarGoogle Scholar
  102. [102] Jemni M. and Elghoul O.. 2008. A system to make signs using collaborative approach. In Proceedings of the International Conference on Computers Helping People with Special Needs (ICCHP’08). Lecture Notes in Computer Science, Vol. 5105, K. Miesenberger, J. Klaus, W. Zagler, and A. Karshmer (eEds.). Springer, Berlin,. Google ScholarGoogle ScholarDigital LibraryDigital Library
  103. [103] Othman A., Assistive M., Elghoul O., Jemni M., and Educational A. L.. 2010. SportSign: A service to make sports news accessible to deaf persons in sign languages. In Proceedings of the International Conference on Computers Helping People with Special Needs. (ICCHP’08). Springer, Berlin. Google ScholarGoogle ScholarCross RefCross Ref
  104. [104] Braffort A., Filhol M., Delorme M., and Bolot L.. 2015. KAZOO: A sign language generation platform based on production rules. Univ. Access Inf. Soc. Google ScholarGoogle ScholarDigital LibraryDigital Library
  105. [105] Filhol M. and Hadjadj M. N.. 2015. A rule triggering system for automatic text-to-sign translation. Univ. Access Inf. Soc. (2015). Google ScholarGoogle ScholarDigital LibraryDigital Library
  106. [106] David Bastien and Pierrette Bouillon Valentin C.. 2018. Prototype of automatic translation to the sign language of French-speaking Belgium. Eval. Deaf Commun. Model. Meas. Contr. C 79, 4 (2018), 162167.Google ScholarGoogle ScholarCross RefCross Ref
  107. [107] Bungeroth J. and Ney H.. 2004. Statistical sign language translation. In Proceedings of the International Conference on Language Resources and Evaluation and Workshop on Representation and Processing of Sign Languages (LREC’04), 105108.Google ScholarGoogle Scholar
  108. [108] Bungeroth J. and Ney H.. 2006. Automatic generation of German Sign Language glosses from German words. In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 3881, 4952. Google ScholarGoogle ScholarDigital LibraryDigital Library
  109. [109] Stein D., Jan B., and Ney H.. 2006. Morpho-syntax based statistical methods for automatic sign language translation. In Proceedings of the 11th Annual Conference of the European Association for Machine Translation (EAMT’06), 169177.Google ScholarGoogle Scholar
  110. [110] Ebling S. and Glauert J.. 2016. Building a Swiss German Sign Language avatar with jasigning and evaluating it among the deaf community. Univ. Access Inf. Soc. 15, 4 (2016), 577587. Google ScholarGoogle ScholarDigital LibraryDigital Library
  111. [111] Ebling S. and Glauert J.. 2013. Exploiting the full potential of JASigning to build an avatar signing train announcements. In Proceedings of the 3rd International Symposium on Sign Language Translation and Avatar Technology. Google ScholarGoogle ScholarCross RefCross Ref
  112. [112] Ebling S.. 2016. Automatic Translation from German to Synthesized Swiss German Sign Language. Ph.D. Dissertation, University of Zurich.Google ScholarGoogle Scholar
  113. [113] Rayner M., Bouillon P., Gerlach J., Strasly I., Tsourakis N., and Ebling S.. 2016. An open web platform for rule-based speech-to-sign translation. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL’16), Short Papers, 162168. Google ScholarGoogle ScholarCross RefCross Ref
  114. [114] Stoll S., Camgoz N. C., Hadfield S., and Bowden R.. 2018. Sign language production using neural machine translation and generative adversarial networks. In Proceedings of the British Machine Vision Conference (BMVC’18), 112.Google ScholarGoogle Scholar
  115. [115] Stoll S., Camgoz N. C., Hadfield S., and Bowden R.. 2020. Text2Sign: Towards sign language production using neural machine translation and generative adversarial networks. Int. J. Comput. Vis. 128, 4 (2020), 891908. Google ScholarGoogle ScholarDigital LibraryDigital Library
  116. [116] Efthimiou E., Sapountzaki G., Karpouzis K., and Fotinea S. E.. 2004. Developing an e-learning platform for the Greek Sign Language. In International Conference on Computers Helping People with Special Needs (ICCHP’04), K. Miesenberger, J. Klaus, W. L. Zagler, D. Burger (Eds.), Lecture Notes in Computer Science, Vol. 3118. Springer, Berlin. Google ScholarGoogle ScholarCross RefCross Ref
  117. [117] Fotinea S. E., Efthimiou E., and Kouremenos D.. 2005. Generating linguistic content for Greek to GSL conversion. In Proceedings of the 7th Hellenic European Conference on Computer Mathematics and Its Applications (HERCMA’05), 2224.Google ScholarGoogle Scholar
  118. [118] Kouremenos D., Fotinea S. E., Efthimiou E., and Ntalianis K.. 2010. A prototype greek text to Greek Sign Language conversion system. Behav. Inf. Technol. 29, 5 (2010), 467481. Google ScholarGoogle ScholarDigital LibraryDigital Library
  119. [119] Efthimiou E., Fotinea S. E., Dimou A. L., Goulas T., and Kouremenos D.. 2015. From grammar-based MT to post-processed SL representations. Univ. Access Inf. Soc. 15, 4 (2015), 499511. Google ScholarGoogle ScholarDigital LibraryDigital Library
  120. [120] Kouremenos D., Ntalianis K., and Kollias S.. 2018a. A novel rule based machine translation scheme from Greek to Greek Sign Language: Production of different types of large corpora and language models evaluation. Comput. Speech Lang 51 (2018), 110135. Google ScholarGoogle ScholarCross RefCross Ref
  121. [121] Kouremenos D., Ntalianis K., Siolas G., and Stafylopatis A.. 2018b. Statistical machine translation for Greek to Greek Sign Language using parallel corpora produced via rule-based machine translation. In CEUR Workshop Proceedings, Vol. 2252, 2842.Google ScholarGoogle Scholar
  122. [122] Falletto A., Prinetto P., and Tiotto G.. 2009. An avatar-based Italian Sign Language visualization system. In Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering. 154160. Google ScholarGoogle ScholarCross RefCross Ref
  123. [123] Prinetto P., Tiotto G., and Del Principe A.. 2009. Designing health care applications for the deaf. In Proceedings of the 3rd International Conference on Pervasive Computing Technologies for Healthcare (PCTHealth’09). Google ScholarGoogle ScholarCross RefCross Ref
  124. [124] Lombardo V., Nunnari F., and Damiano R.. 2010. A virtual interpreter for the Italian Sign Language. In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 6356, 201207. Google ScholarGoogle ScholarCross RefCross Ref
  125. [125] Lombardo V., Battaglino C., Damiano R., and Nunnari F.. 2011. An avatar-based interface for the Italian Sign Language. In Proceedings of the International Conference on Complex, Intelligent and Software Intensive Systems (CISIS’11), 589594. Google ScholarGoogle ScholarDigital LibraryDigital Library
  126. [126] Barberis D., Garazzino N., Prinetto P., and Tiotto G.. 2011. Improving accessibility for deaf people: An editor for computer assisted translation through virtual avatars. In Proceedings of the 13th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS’11), 253254. Google ScholarGoogle ScholarDigital LibraryDigital Library
  127. [127] Mazzei A., Lesmo L., Battaglino C., Vendrame M., and Bucciarelli M.. 2013. Deep natural language processing for Italian Sign Language translation. In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 8249, 193204. Google ScholarGoogle ScholarDigital LibraryDigital Library
  128. [128] Haseeb A. A. and Ilyas A.. 2012. Speech Translation into Pakistan Sign Language. Ph.D. Dissertation.Google ScholarGoogle Scholar
  129. [129] Abbas A. and Sarfraz S.. 2018. Developing a prototype to translate text and speech to Pakistan sign language with bilingual subtitles: A framework. J. Educ. Technol. Syst. 47, 2 (2018), 248266. Google ScholarGoogle ScholarCross RefCross Ref
  130. [130] Gul A., Zehra B., Shah S., Javed N., and Saleem M. I.. 2020. Two-way smart communication system for deaf dumb and normal people. In Proceedings of the 2nd International Conference on Information Science and Communication Technology (ICISCT’20), 14. Google ScholarGoogle ScholarCross RefCross Ref
  131. [131] Khan N. S., Abid A., and Abid K.. 2020. A novel natural language processing (NLP)–based machine translation model for English to Pakistan Sign Language translation. Cogn. Comput. 12, 4 (2020), 748765. Google ScholarGoogle ScholarCross RefCross Ref
  132. [132] Rabia Yorgancı, Kındıroǧlu A. A., and Akarun L.. 2016. Avatar-based sign language training interface for primary school education. In Proceedings of the Graphical and Robotic Embodied Agents for Therapeutic Systems (GREATS’16).Google ScholarGoogle Scholar
  133. [133] Eryiğit C., Köse H., Kelepir M., and Eryiğit G.. 2016. Building machine-readable knowledge representations for Turkish Sign Language generation. Knowl.-Bas. Syst. 108 (2016), 179194. Google ScholarGoogle ScholarDigital LibraryDigital Library
  134. [134] Selcuk-Simsek M. and Cicekli I.. 2017. Bidirectional machine translation between Turkish and Turkish Sign Language: A data-driven approach. Int. J. Nat. Lang. Comput. 6, 3 (2017), 3346. Google ScholarGoogle ScholarCross RefCross Ref
  135. [135] Buz B. and Gungor T.. 2019. Developing a statistical Turkish Sign Language translation system for primary school students. In Proceedings of the IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA’19), Google ScholarGoogle ScholarCross RefCross Ref
  136. [136] Kayahan D. and Gungor T.. 2019a. A hybrid translation system from Turkish spoken language to Turkish Sign Language. In Proceedings of the IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA’19), Google ScholarGoogle ScholarCross RefCross Ref
  137. [137] Kayahan D.. 2019b. Hybrid Translation System from Turkish Spoken Language to Turkish Sign Language. Ph. D. Dissertation, Bogazici University.Google ScholarGoogle ScholarCross RefCross Ref
  138. [138] Gümüşçekiçci G., Ezerceli Ö., and Tek F. B.. 2020. Web service translating content into Turkish Sign Language. In Proceedings of the 5th International Conference on Computer Science and Engineering (UBMK’20), 355–259. Google ScholarGoogle ScholarCross RefCross Ref
  139. [139] Dangsaart S. and Cercone N.. 2007. Bridging the gap: Thai-Thai sign machine translation. In Proceedings of the 10th Conference of the Pacific Association for Computational Linguistics, 191199.Google ScholarGoogle Scholar
  140. [140] Dangsaart S., Naruedomkul K., Cercone N., and Sirinaovakul B.. 2008. Intelligent thai text—Thai sign translation for language learning. Comput. Educ. 51, 3 (2008), 11251141. Google ScholarGoogle ScholarDigital LibraryDigital Library
  141. [141] Dangsaart S.. 2013. Thai text-Thai sign translation application (T3STA). In Computational Approaches to Assistive Technologies for People with Disabilities, Frontiers in Artificial Intelligence and Applications, Vol. 253, 5164. Google ScholarGoogle ScholarCross RefCross Ref
  142. [142] Vichyaloetsiri T. and Wuttidittachotti P.. 2017. Web service framework to translate text into sign language. In Proceedings of the International Conference on Computer, Information and Telecommunication Systems (CITS’17), 180184. Google ScholarGoogle ScholarCross RefCross Ref
  143. [143] Bento J., Claudio A. P., and Urbano P.. 2014. Avatars on Portuguese sign language. 2014 9th Iberian Conference on Information Systems and Technologies (CISTI'14), 1--7. Google ScholarGoogle ScholarCross RefCross Ref
  144. [144] Almeida I.. 2014a. Exploring Challenges in Avatar-based Translation from European Portuguese to Portuguese Sign Language. 110.Google ScholarGoogle Scholar
  145. [145] Almeida I.. 2014b. Exploring challenges in avatar-based translation from European Portuguese to Portuguese Sign Language. Retrieved December 14, 2020 from http://web.ist.utl.pt/∼ist163556/pt2lgp/shortv.pdf.Google ScholarGoogle Scholar
  146. [146] Almeida I., Coheur L., and Candeias S.. 2015a. Coupling natural language processing and animation synthesis in Portuguese Sign Language Translation. In Proceedings of the 2015 Workshop on Vision and Language (VL'15), 94--103. https://aclanthology.org/W15-2815/.Google ScholarGoogle Scholar
  147. [147] Almeida I., Coheur L., and Candeias S.. 2015b. From European Portuguese to Portuguese Sign Language. In Proceedings of SLPAT 2015: 6th Workshop on Speech and Language Processing for Assistive Technologies, 140--143. https://aclanthology.org/W15-5124.Google ScholarGoogle Scholar
  148. [148] Escudeiro P., Escudeiro N., Reis R., Lopes J., Norberto M., Baltasar A. B., Barbosa M., and Bidarra J.. 2015. Virtual sign—A real time bidirectional translator of Portuguese Sign Language. Proc. Comput. Sci. 67 (2015), 252262. Google ScholarGoogle ScholarCross RefCross Ref
  149. [149] Van Zijl L.. 2006. South African Sign Language machine translation project. In Proceedings of the 8th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS’06), 233234. Google ScholarGoogle ScholarDigital LibraryDigital Library
  150. [150] Van Zijl L. and Combrink A.. 2006. The South African Sign Language machine translation project: Issues on non-manual sign generation. In ACM International Conference Proceeding Series, Vol. 204, 127134. Google ScholarGoogle ScholarDigital LibraryDigital Library
  151. [151] Welgemoed J.. 2007. A Prototype System for Machine Translation from English to South African Sign Language Using Synchronous Tree Adjoining Grammars. Ph.D. Dissertation.Google ScholarGoogle Scholar
  152. [152] Kanis J., Zahradil J., Jurčíček F., and Müller L.. 2006. Czech-sign speech corpus for semantic based machine translation. In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 4188, 613620. Google ScholarGoogle ScholarDigital LibraryDigital Library
  153. [153] Krňoul Z., Kanis J., Železný M., and Müller L.. 2008. Czech text-to-sign speech synthesizer. In Machine Learning for Multimodal Interaction (MLMI’07), Lecture Notes in Computer Science, Vol. 4892, A. Popescu-Belis, S. Renals, H. Bourlard (Eds.). Springer, Berlin. Google ScholarGoogle ScholarCross RefCross Ref
  154. [154] Kwon K.-H., Woo Y.-S., and Min H.-K.. 2000. Design and implementation of a Koran text to sign language translation system. Kor. Inf. Process. Soc. J. 7, 3 (2000), 756765.Google ScholarGoogle Scholar
  155. [155] Choi J. W., Lee H. J., and Park J. C.. 2005. From text to sign language: Exploiting the spatial and motioning dimension. In Proceedings of the 19th Pacific Asia Conference on Language, Information and Computation (PACLIC’19).Google ScholarGoogle Scholar
  156. [156] Chen Y. J., Chiu Y. H., Wu C. H., and Cheng C. J.. 2005. Development of Video Synthesis Based Taiwanese Sign Communication-Aided System. 263265.Google ScholarGoogle Scholar
  157. [157] Wu C. H., Su H. Y., Chiu Y. H., and Lin C. H.. 2007. Transfer-based statistical translation of Taiwanese Sign Language using PCFG. ACM Trans. As. Lang. Inf. Process. 6, 1 (2007), 118. Google ScholarGoogle ScholarDigital LibraryDigital Library
  158. [158] Punchimudiyanse M. and Meegama R. G. N.. 2016. 3D signing avatar for Sinhala Sign Language. In Proceedings of the IEEE 10th International Conference on Industrial and Information Systems (ICIIS’15), 290295. Google ScholarGoogle ScholarCross RefCross Ref
  159. [159] Punchimudiyanse M. and Meegama R. G. N.. 2017. Computer interpreter for translating written Sinhala to Sinhala Sign Language. OUSL J. 12, 1 (2017), 70. Google ScholarGoogle ScholarCross RefCross Ref
  160. [160] Lozynska O., Davydov M., Pasichnyk V., and Veretennikova N.. 2019a. Rule-based machine translation into Ukrainian Sign Language using concept dictionary. In CEUR Workshop Proceedings, Vol. 2387, 191201.Google ScholarGoogle Scholar
  161. [161] Olga L., Valeriia S., and Volodymyr P.. 2019b. The sign translator information system for tourist. In Proceedings of the IEEE 14th International Scientific and Technical Conference on Computer Sciences and Information Technologies (CSIT’19), 162165. Google ScholarGoogle ScholarCross RefCross Ref
  162. [162] Grif M. G., Korolkova O. O., Demyanenko Y. A., and Tsoy Y. B.. 2011. Development of computer sign language translation technology for deaf people. In Proceedings of the 6th International Forum on Strategic Technology (IFOST’11), 674677. Google ScholarGoogle ScholarCross RefCross Ref
  163. [163] Grif M. G., Korolkova O. O., Demyanenko Y. A., and Tsoy E. B.. 2012. Computer sign language translation system for hearing impaired users. In Proceedings of the 7th International Forum on Strategic Technology (IFOST’12), Google ScholarGoogle ScholarCross RefCross Ref
  164. [164] Morrissey S. and Way A.. 2007. Joining hands: Developing a sign language machine translation system with and for the deaf community. In CEUR Workshop Proceedings, Vol. 415.Google ScholarGoogle Scholar
  165. [165] Morrissey S.. 2008a. Assistive translation technology for deaf people : Translating into and animating Irish Sign Language. Retrieved March 18, 2021 from https://www.semanticscholar.org/paper/Assistive-translation-technology-for-deaf-people%3A-Morrissey/18d3ca7ad64eaba641a6b8ec2e72295188527f01.Google ScholarGoogle Scholar
  166. [166] Morrissey S.. 2008b. Data-driven Machine Translation for Sign Languages. Ph.D. DissertationGoogle ScholarGoogle Scholar
  167. [167] Verlinden M., Tijsseling C., and Frowein H.. 2002. A signing avatar on the WWW. In Gesture and Sign Language in Human-Computer Interaction. GW 2001. Lecture Notes in Computer Science(), I. Wachsmuth and T. Sowa (Eds.). Vol. 2298, Springer, Berlin, Heidelberg. Google ScholarGoogle ScholarCross RefCross Ref
  168. [168] Morrissey S. and Way A.. 2005. An example-based approach to translating sign language. In MTSUMMIT. https://www.aclanthology.org/2005.mtsummit-ebmt.14.pdf.Google ScholarGoogle Scholar
  169. [169] Francik J. and Fabian P.. 2002. Animating sign language in the real time. In Applied Informatics-Proceedings. 276281. https://www.researchgate.net/publication/2494990_Animating_Sign_Language_in_the_Real_Time.Google ScholarGoogle Scholar
  170. [170] Suszczańska N., Szmal P., and Francik J.. 2002. Transtlating polish texts into sign language in the TGT system. In Proceedings of the 20th International Multiconference on Applied Informatics. 282287.Google ScholarGoogle Scholar
  171. [171] Suszczanska N., Szmal P., and Kulikow S.. 2007. Continuous text translation using text modeling in the Thetos system. Int. J. Comput. Inf. Eng. 1, 8 (2007), 26382641. http://scholar.waset.org/1307-6892/4171. Accessed 18 March 2021.Google ScholarGoogle Scholar
  172. [172] Sagawa H. and Takeuchi M.. 2002. A teaching system of Japanese Sign Language using sign language recognition and generation. In Proceedings of the ACM International Multimedia Conference and Exhibition. 137145. Google ScholarGoogle ScholarCross RefCross Ref
  173. [173] Mean Foong O., Low T. J., and La W. W.. 2009. V2S: Voice to sign language translation system for Malaysian deaf people. In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 5857, 868876. Google ScholarGoogle ScholarDigital LibraryDigital Library
  174. [174] Da Q. L., Khang N. H. D., and Ngon N. C.. 2019. Converting the Vietnamese television news into 3D sign language animations for the deaf. In Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, Vol. 257. Springer International Publishing. Google ScholarGoogle ScholarCross RefCross Ref
  175. [175] Shamsi M., Divani M., and Kenari A. R.. 2020. Designing an avatar-based translator system from Persian into Persian Sign Language (PSL). Technol. Educ. J 1 (2020), 114.Google ScholarGoogle Scholar
  176. [176] Trujillo-Romero F. and Caballero-Morales S.-O.. 2012. Towards the development of a Mexican speech-to-sign-language translator for the deaf community. Acta Univ. 22 (2012), 8389. Google ScholarGoogle ScholarCross RefCross Ref
  177. [177] Costa A. R., Dimuro G. P., et al. 2001. Supporting deaf sign languages in written form on the web. In Proceedings of the 10th World Wide Web Conference.Google ScholarGoogle Scholar
  178. [178] Lebert M.. 2008. Project Gutenberg (1971--2008). University of Toronto and Project Gutenberg. EBook #27045. https://www.gutenberg.org/ebooks/27045.Google ScholarGoogle Scholar
  179. [179] Prillwitz S., Leven R., Zienert H., Hamke T., and Henning J.. 1989. HamNoSys Version 2.0: Hamburg Notation System for Sign Languages: An Introductory Guide, International Studies on Sign Language and Communication of the Deaf, Vol. 5. Signum Press, Hamburg, Germany.Google ScholarGoogle Scholar
  180. [180] Hanke T.. 2004. HamNoSys–Representing sign language data in language resources and language processing contexts. In Workshop Proceedings: Representation and Processing of Sign Languages (LREC’04), 16.Google ScholarGoogle Scholar
  181. [181] Roth R., Rambow O., Habash N., Diab M., and Rudin C.. 2008. Arabic morphological tagging, diacritization, and lemmatization using lexeme models and feature ranking. In Proceedings of ACL-08: HLT, Short Papers. 15–20 and 11—120.Google ScholarGoogle ScholarCross RefCross Ref
  182. [182] Pasha A., Al-Badrashiny M., Diab M., El Kholy A., Eskander R., Habash N., Pooleery M., Rambow O., and Roth R. M.. 2014. MADAMIRA: A fast, comprehensive tool for morphological analysis and disambiguation of Arabic. In Proceedings of the 9th International Conference on Language Resources and Evaluation (LREC’14), 10941101.Google ScholarGoogle Scholar
  183. [183] Boudlal A., Lakhouaja A., Mazroui A., Meziane A., Ould Abdallahi Ould Bebah M., and Shoul M.. 2010. Alkhalil morpho sys: A morpho-syntactic analysis system for Arabic texts. In Proceedings of the International Arab Conference on Information Technology (ACIT'10).Google ScholarGoogle Scholar
  184. [184] Souteh Y. and Bouzoubaa K.. 2011. SAFAR platform and its morphological layer. In Proceeding of the 11th International Conference on Language Engineering (ESOLEC’11), 1415.Google ScholarGoogle Scholar
  185. [185] Sleator D. and Temperley D.. 1991. Parsing English with a Link Grammar. Carnegie Mellon University Computer Science Technical Report CMU-CS-91–196.Google ScholarGoogle Scholar
  186. [186] Kamp H. and Reyle U.. 1993. From discourse to logic. Introduction to Model Theoretic Semantics of Natural Language, Formal Logic and Discourse Representation Theory. Kluwer Academic.Google ScholarGoogle Scholar
  187. [187] Pollard C. and Sag I. A.. 1994. Head-Driven Phrase Structure Grammar. The University of Chicago Press, Chicago.Google ScholarGoogle Scholar
  188. [188] Elliott R., Glauert J., Jennings V., and Kennaway J.. 2004. An overview of the SiGML notation and SiGML signing software system. In Proceedings of the 4th International Conference on Language Resources and Evaluation (LREC’04).Google ScholarGoogle Scholar
  189. [189] eSIGN Project. 2004. Retrieved March 1, 2022 from https://www.sign-lang.uni-hamburg.de/esign.Google ScholarGoogle Scholar
  190. [190] Beule J. D. and Steels L.. 2005. Hierarchy in fluid construction grammar. In Proceedings of the 28th Annual German Conference on AI, (KI’05), Lecture Notes in Artificial Intelligence, Vol. 3698, Furbach, Ulrich (ed.). Springer, Berlin, 115.Google ScholarGoogle ScholarDigital LibraryDigital Library
  191. [191] Lin D.. 1998. Dependency-based evaluation of MINIPAR. In Workshop on the Evaluation of Parsing Systems.Google ScholarGoogle Scholar
  192. [192] Kaplan R. M.. 1989. The formal architecture of lexical-functional grammar. J. Inf. Sci. Eng. 5 (1989), 305–22.Google ScholarGoogle Scholar
  193. [193] Klein D. and Manning C. D.. 2003. Accurate unlexicalized parsing. In Proceedings of the 41st Annual Meeting on Association for Computational Linguistics, Association for Computational Linguistics, New York, NY, 423430.Google ScholarGoogle ScholarDigital LibraryDigital Library
  194. [194] Koehn P.. 2012. Moses: Statistical Machine Translation System User Manual and Code Guide. Retrieved March 22, 2021 from http://www.statmt.org/moses/manual/X.pdf.Google ScholarGoogle Scholar
  195. [195] Casacuberta F. and Vidal E.. 2004. Machine translation with inferred stochastic finite-state transducers. Comput. Linguist. 30, 2 (2004), 205225.Google ScholarGoogle ScholarDigital LibraryDigital Library
  196. [196] Efthimiou E., Fotinea S.-E., Hanke T., Glauert J., Bowden R., Braffort A., Collet C., Maragos P., and Lefebvre-Albaret F.. 2012. Sign language technologies and resources of the dicta-sign project. In Proceedings of the 5th Workshop on the Representation and Processing of Sign Languages: Interactions between Corpus and Lexicon, Satellite Workshop to the 8th International Conference on Language Resources and Evaluation (LREC’12), ELRA, 3744.Google ScholarGoogle Scholar
  197. [197] Filhol M.. 2012. Combining two synchronisation methods in a linguistic model to describe sign language. In Gesture and Sign Language in Human–Computer Interaction and Embodied Communication, LNCS/LNAI, Vol. 7206, E. Efthimiou, G. Kouroupetroglou, and S.-E. Fotinea (Eds.). Springer, Berlin, 194203.Google ScholarGoogle ScholarDigital LibraryDigital Library
  198. [198] Braffort A., Bolot L., Segouat J.. 2011. Virtual signer coarticulation in octopus, a sign language generation platform. In Proceedings of the 9th International Gesture Workshop (GW’11): Gesture in Embodied Communication and Human–Computer Interaction, E. Efthimiou, G. Kouroupetroglou (Eds.). ILSP/ATHENA RC and National and Kapodistrian University of Athens. 2932Google ScholarGoogle Scholar
  199. [199] Delorme M., Filhol M., and Braffort A.. 2012. Thumb modelling for the generation of sign language. In Gesture and Sign Language in Human Computer Interaction and Embodied Communication, LNCS/LNIA, Vol. 7206, E. Efthimiou, G. Kouroupetroglou, S.-E. Fotinea (Eds.). Springer, Berlin, 151160.Google ScholarGoogle Scholar
  200. [200] Bertoldi N., Tiotto G., Prinetto P., Piccolo E., Nunnari F., Lombardo V., Damiano R., Lesmo L., and Principe A. D.. 2010. On the creation and annotation of a large-scale italian-lis parallel corpus. In Proceedings of the 4th Workshop on the Representation and Processing of Sign Languages: Corpora and Sign Language Technologies (CSLT’10).Google ScholarGoogle Scholar
  201. [201] Özenç B. and Solak E.. 2020. Visual modeling of turkish morphology. In Proceedings of the 12th Conference on Language Resources and Evaluation (LREC’20), 39843990.Google ScholarGoogle Scholar
  202. [202] Joshi A. and Schabes Y.. 1997. Handbook of Formal Languages. Springer-Verlag.Google ScholarGoogle Scholar
  203. [203] Newkirk D.. 1986. Outline of a Proposed Orthography of American Sign Language. Retrieved March 22, 2021 from http://members.home.net/dnewkirk/signfont/orthog.htm.Google ScholarGoogle Scholar
  204. [204] Stroppa N. and Way A.. 2006. MaTrEx: DCU machine translation system for IWSLT 2006. In Proceedings of the International Workshop on Spoken Language Translation. 3136.Google ScholarGoogle Scholar
  205. [205] Hemphill C., Godfrey J., and Doddington G.. 1990. The ATIS spoken language systems pilot corpus. In Proceedings of the Workshop on Speech and Natural Language. 96101.Google ScholarGoogle Scholar
  206. [206] Bragg D., Koller O., Bellard M., Berke L., Boudreault P., Braffort A., Caselli N., Huenerfauth M., Kacorri H., Verhoef T., et al. 2019. Sign language recognition, generation, and translation: An interdisciplinary perspective. In Proceedings of the 21st International ACM SIGACCESS Conference on Computers and Accessibility. 1631Google ScholarGoogle ScholarDigital LibraryDigital Library
  207. [207] Duarte A.. 2019. Cross-modal neural sign language translation. In Proceedings of the 27th ACM International Conference on Multimedia, 16501654. Google ScholarGoogle ScholarDigital LibraryDigital Library
  208. [208] Wadhawan A. and Kumar P.. 2021. Sign language recognition systems: A decade systematic literature review. Arch. Computat. Methods Eng. 28 (2021), 785813. Google ScholarGoogle ScholarCross RefCross Ref
  209. [209] Farooq U., Rahim M. S. M., Sabir N., et al. 2021. Advances in machine translation for sign language: Approaches, limitations, and challenges. Neural Comput. Appl. 33 (2021), 1435714399. Google ScholarGoogle ScholarDigital LibraryDigital Library
  210. [210] Kahlon N. K. and Singh W.. 2021. Machine translation from text to sign language: A systematic review. Univ. Access Inf. Soc. (2021). Google ScholarGoogle ScholarDigital LibraryDigital Library
  211. [211] Kumar R., Goyal V., and Goyal L.. 2020. Airport announcement system for deaf. In Proceedings of the 17th International Conference on Natural Language Processing on Natural Language Processing, 1821 https://aclanthology.org/2020.icon-demos.15.pdf.Google ScholarGoogle Scholar
  212. [212] Kumar R., Goyal V., and Goyal L.. 2020. Railway stations announcement system for deaf. In Proceedings of the 17th International Conference on Natural Language Processing on Natural Language Processing. 1821Google ScholarGoogle Scholar
  213. [213] Kumar R., Goyal V., and Goyal L.. 2021. Comparative analysis of automatic sign language generation systems. J. Sci. Res. 65, 5 (2021), 226235. Google ScholarGoogle ScholarCross RefCross Ref
  214. [214] Papastratis I., Chatzikonstantinou C., Konstantinidis D., Dimitropoulos K., and Daras P.. 2021. Artificial intelligence technologies for sign language. Sensors 21 (2021), 5843. Google ScholarGoogle ScholarCross RefCross Ref
  215. [215] Adeyanju I. A., Bello O. O., and Adegboye M. A.. 2021. Machine learning methods for sign language recognition: A critical review and analysis. Intell. Syst. Appl. 12 (2021), 200056. Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. State of the Art of Automation in Sign Language: A Systematic Review

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in

    Full Access

    • Published in

      cover image ACM Transactions on Asian and Low-Resource Language Information Processing
      ACM Transactions on Asian and Low-Resource Language Information Processing  Volume 22, Issue 4
      April 2023
      682 pages
      ISSN:2375-4699
      EISSN:2375-4702
      DOI:10.1145/3588902
      Issue’s Table of Contents

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 6 April 2023
      • Online AM: 29 September 2022
      • Accepted: 14 September 2022
      • Revised: 1 September 2022
      • Received: 22 May 2021
      Published in tallip Volume 22, Issue 4

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • research-article
    • Article Metrics

      • Downloads (Last 12 months)303
      • Downloads (Last 6 weeks)45

      Other Metrics

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Full Text

    View this article in Full Text.

    View Full Text

    HTML Format

    View this article in HTML Format .

    View HTML Format
    About Cookies On This Site

    We use cookies to ensure that we give you the best experience on our website.

    Learn more

    Got it!