Universal Access in the Information Society

, Volume 15, Issue 4, pp 551–566 | Cite as

An automated technique for real-time production of lifelike animations of American Sign Language

  • John McDonaldEmail author
  • Rosalee Wolfe
  • Jerry Schnepp
  • Julie Hochgesang
  • Diana Gorman Jamrozik
  • Marie Stumbo
  • Larwan Berke
  • Melissa Bialek
  • Farah Thomas
Long paper


Generating sentences from a library of signs implemented through a sparse set of key frames derived from the segmental structure of a phonetic model of ASL has the advantage of flexibility and efficiency, but lacks the lifelike detail of motion capture. These difficulties are compounded when faced with real-time generation and display. This paper describes a technique for automatically adding realism without the expense of manually animating the requisite detail. The new technique layers transparently over and modifies the primary motions dictated by the segmental model and does so with very little computational cost, enabling real-time production and display. The paper also discusses avatar optimizations that can lower the rendering overhead in real-time displays.


Sign Language Inverse Kinematic American Sign Inverse Kinematic Solution Sign Synthesis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors would like to thank the Deaf experts and qualified interpreters for reviewing drafts of the animations. We are also grateful to the reviewers for their thoughtful comments and valuable feedback.


  1. 1.
    Courty, N., Gibet, S.: Why is the creation of a virtual signer challenging computer. In: Boulic, R., Chrysanthou, Y., Komura, T. (eds.), pp. 290–300. Springer, Utrecht (2010)Google Scholar
  2. 2.
    Delorme, M.: Modelisation du squelette pour la generation realiste de postures de la lange de signes francaise. Ph.D. Dissertation, Laboratoire d’Informatique pour la Mechanique et les Sciences de L’Ingenieur (LIMSI) (2011)Google Scholar
  3. 3.
    Delorme, M., Filhol, M., Braffort, A.: Animation generation process for sign language synthesis. In: Advances in Computer–Human Interactions, ACHI ‘09, pp. 386–390 (2009)Google Scholar
  4. 4.
    Efthimiou, E., Fotinea, S.-E., Vogler, C., Hanke, T., Glauert, J., Bowden, R., Segouat, J.: Sign language recognition, generation, and modelling: a research effort with applications in deaf communication. In: Universal Access in Human–Computer Interaction, Addressing Diversity. Lecture Notes in Computer Science, vol 5614, pp. 21–30 (2009)Google Scholar
  5. 5.
    Elliott, R., Glauert, J., Kennaway, J., Marshall, I., Safar, E.: Linguistic modelling and language-processing technologies for Avatar-based sign language presentation. Univ. Access Inf. Soc. 6(4), 375–391 (2008)CrossRefGoogle Scholar
  6. 6.
    Filhol, M.: A combination of two synchronisation methods to formalise sign language animation. In: Proceedings of the 9th International Gesture Workshop (2011)Google Scholar
  7. 7.
    Gibet, S., Courty, N., Duarte, K., Le Naour, T.: The SignCom system for data-driven animation of interactive virtual signers: methodology and evaluation. ACM Trans. Interact Intell. Syst. (TiiS) 1(1), 1–26 (2011)CrossRefGoogle Scholar
  8. 8.
    Hanke, T., Matthes, S., Regen, A., Storz, J., Satu, W., Elliott, R., Kennaway, R.: Using Timing Information to Improve the Performance of Avatars. Second International Workshop on Sign Language Translation and Avatar Technology (SLTAT), Dundee, Scotland, UK (2011)Google Scholar
  9. 9.
    Huenerfauth, M., Lu, P., Rosenberg, A.: Evaluating importance of facial expression in American Sign Language and pidgin signed English animations. In: The Proceedings of the 13th International ACM SIGACCESS Conference on Computers and Accessibility,pp. 99–106. Association For Computing Machinery, New York (2011)Google Scholar
  10. 10.
    Johnson, R.E., Liddell, S.K.: A segmental framework for representing signs phonetically. Sign Lang. Stud. 11(3), 408–463 (2011)CrossRefGoogle Scholar
  11. 11.
    Johnston, O., Thomas, F.: The illusion of life: disney animation. Random House (Disney Press), New York (1995)Google Scholar
  12. 12.
    Kacorri, H., Lu, P., Huenerfauth, M.: Effect of displaying human videos during an evaluation study of American Sign Language animation. ACM Trans. Access. Comput. (TACCESS) 5(2), 4 (2013)Google Scholar
  13. 13.
    Lasseter, J.: Principles of traditional animation applied to 3D computer animation. In: SIGGRAPH ‘87 Proceedings of the 14th Annual Conference on Computer Graphics and Interactive Techniques, pp. 35–44. Association of Computing Machinery, Anaheim, California (1987)Google Scholar
  14. 14.
    McDonald, J., Alkoby, K., Carter, R., Christopher, J., Davidson, M., Ethridge, D., Wolfe, R.: A direct method for positioning the arms of a human model. In: Proceedings of Graphics Interface, pp. 99–106. Calgary, Alberta Canada (2002)Google Scholar
  15. 15.
    Metzger, M.: Constructed dialogue and constructed action in American Sign Language. In: Lucas, C. (ed.) The Sociolinguistics in Deaf Communities, pp. 255–271. Gaullaudet University Press, Washington (1995)Google Scholar
  16. 16.
    Napoli, R., Gloman, C.: Scene Design and Lighting Techniques: A Basic Guide for Theatre. Focal Press, Burlington (2007)Google Scholar
  17. 17.
    Paolo, B., Ronan, B.: An inverse kinematics architecture enforcing an arbitrary number of strict priority levels. Vis. Comput. 20(6), 402–417 (2004)CrossRefGoogle Scholar
  18. 18.
    Perlin, K.: A system for scripting interactive actors in virtual worlds. In: Proceedings of ACM SIGGRAPH 96, pp. 205–216. Association for Computing Machinery, New Orleans (1996)Google Scholar
  19. 19.
    Phong, T.: Illumination for computer generated pictures. Commun. ACM 18(6), 311–317 (1975)CrossRefGoogle Scholar
  20. 20.
    Poor, G.: ASL video dictionary and inflection guide. (2008). Retrieved 15 May 2011
  21. 21.
    Reese, N.B.: Joint Range of Motion and Muscle Length Testing. Elsevier, St. Louis (2010)Google Scholar
  22. 22.
    Saladin, K.: Human Anatomy. McGraw-Hill, New York (2007)Google Scholar
  23. 23.
    Schnepp, J. (2012). A representation of selected nonmanual signals in American Sign Language. DePaul University: ProQuest Dissertations and ThesesGoogle Scholar
  24. 24.
    Schnepp, J., Wolfe, R., Shiver, B., McDonald, J., Toro, J.: SignQUOTE: a remote testing facility for eliciting signed qualitative feedback. In: Second International Workshop on Sign Language Translation and Avatar Technology (SLTAT). (2011). Retrieved 23 Apr 2012
  25. 25.
    Shoemake, K.: Euler angle conversion. In: Heckbert, P. (ed.) Graphics Gems IV, pp. 222–229. Academic Press, San Diego (1994)CrossRefGoogle Scholar
  26. 26.
    Shreiner, D., Sellers, G., Kessenich, J., Licea-Kane, B.: OpenGL Programming Guide: The Official Guide to Learning OpenGL, Version 4.3, 8th edn. Addison-Wesley Professional, Upper Saddle River (2013)Google Scholar
  27. 27.
    Sozio, S.: The Mastery of Mimodrame: An In-Depth Study of Mime Techniques. Destiny Image Publishers, Shippensburg (1989)Google Scholar
  28. 28.
    Sutton, V. (Ed.): SignWriting for sign languages. From (2014). Retrieved 8 Oct 2014
  29. 29.
    Tolani, D., Goswami, A., Badler, N.: Real-time inverse kinematics techniques for anthropomorphic limbs. Graph. Models 62, 353–388 (2000). doi: 10.1006/gmod.2000.0528 CrossRefzbMATHGoogle Scholar
  30. 30.
    Whitaker, H., Halas, J.: Timing for Animation. Focal Press, Burlington (2008)Google Scholar
  31. 31.
    Wilbur, R.: Phonological and prosodic layering of nonmanuals in American Sign Language. In: Emmorey, K., Lane, H.L., Bellugi, U., Klima, E. (eds.) The Signs of Language Revisited: Festscrift for Ursula Bellugi and Edward Klima, pp. 213–241 (2000)Google Scholar
  32. 32.
    Wolfe, R., Cook, P., McDonald, J., Schnepp, J.: Linguistics as structure in computer animation: toward a more effective synthesis of brow motion in American Sign Language. Sign Lang. Linguist. 14(1), 179–199 (2011)CrossRefGoogle Scholar
  33. 33.
    Wolfe, R., McDonald, J., Schnepp, J.: An Avatar to Depict Sign Language: Building from Reusable Hand Animation. International Workshop on Sign Language Translation and Avatar Technology (SLTAT), Berlin, Germany (2011)Google Scholar
  34. 34.
    Wyvill, B., McPheeters, C., Wyvill, G.: Animating soft objects. Vis. Comput. 2, 235–242 (1986)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • John McDonald
    • 1
    Email author
  • Rosalee Wolfe
    • 1
  • Jerry Schnepp
    • 2
  • Julie Hochgesang
    • 3
  • Diana Gorman Jamrozik
    • 4
  • Marie Stumbo
    • 1
  • Larwan Berke
    • 3
  • Melissa Bialek
    • 1
  • Farah Thomas
    • 1
  1. 1.DePaul UniversityChicagoUSA
  2. 2.Bowling Green State UniversityBowling GreenUSA
  3. 3.Gallaudet UniversityWashingtonUSA
  4. 4.Columbia College ChicagoChicagoUSA

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