Benchmark databases for video-based automatic sign language recognition

Proceedings of the 6th International Conference on Language Resources and Evaluation, LREC 2008

Volumn , Issue , 2008, Pages 1115-1120

  Dreuw, Philippe ^a   Neidle, Carol ^b   Athitsos, Vassilis ^c   Sclaroff, Stan ^b   Ney, Hermann ^a  

^a RWTH AACHEN UNIVERSITY   (Germany)

^b BOSTON UNIVERSITY   (United States)

^c UNIVERSITY OF TEXAS AT ARLINGTON   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

VIDEO RECORDING;

BASELINE RESULTS; BENCHMARK DATABASE; DATABASE ACCESS; DATABASE STATISTICS; RECENT RESEARCHES; SIGN LANGUAGE RECOGNITION; SPEAKER DEPENDENTS; SPECIAL HARDWARE;

DATABASE SYSTEMS;

EID: 85007575883     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (24)

1. R. Bowden, D. Windridge, T. Kadir, A. Zisserman, and M. Brady. 2004. A linguistic feature vector for the visual interpretation of sign language. In European Conf. Computer Vision, volume 1, pages 390-401.
2. P. Dreuw, T. Deselaers, D. Rybach, D. Keysers, and H. Ney. 2006. Tracking using dynamic programming for appearance-based sign language recognition. In IEEE Intl. Conf. on Automatic Face and Gesture Recognition, pages 293-298, Southampton, April.
3. P. Dreuw, D. Rybach, T. Deselaers, M. Zahedi, and H. Ney. 2007a. Speech recognition techniques for a sign language recognition system. In Interspeech 2007, pages 2513-2516, Antwerp, Belgium, August. ISCA best student paper award of Interspeech 2007.
4. P. Dreuw, D. Stein, and H. Ney. 2007b. Enhancing a sign language translation system with vision-based features. In International Workshop on Gesture in Human-Computer Interaction and Simulation, pages 18-20, Lisbon, Portugal, May.
5. U. M. Erdem and S. Sclaroff. 2002. Automatic detection of relevant head gestures in American Sign Language communication. In International Conf. on Pattern Recognition (ICPR), volume 1, pages 460-463.
6. D. Klakow and J. Peters. 2002. Testing the correlation of word error rate and perplexity. Speech Communication, 38:19-28.
7. R. Kneser and H. Ney. 1995. Improved backing-off for mgram language modeling. In IEEE ICASSP, volume 1, pages 49-52, Detroit, MI.
8. A. M. Martinez, R. B. Wilbur, R. Shay, and A. C. Kak. 2002. Purdue RVL-SLLL ASL database for Automatic Recognition of American Sign Language. In IEEE Int. Conf. on Multimodal Interfaces, Pittsburg, PA, USA, October.
9. C. Neidle, S. Sclaroff, and V. Athitsos. 2001. SignstreamTM: A tool for linguistic and computer vision research on visual-gestural language data. Behavior Research Methods, Instruments, and Computers, 3(33):311-320.
10. ™: A database tool for research on visual-gestural language. Journal of Sign Language and Linguistics, 1/2(4):203-214.
11. ™ annotation: Conventions used for the American Sign Language Linguistic Research Project. Technical Report 11, Boston University.
12. ™ annotation: Addendum to conventions used for the American Sign Language Linguistic Research Project. Technical Report 13, Boston University, August.
13. D. Stein, P. Dreuw, H. Ney, S. Morrissey, and A. Way. 2007. Hand in hand: Automatic sign language to speech translation. In 11th Conference on Theoretical and Methodological Issues in Machine Translation (TMI-07), pages 214-220, Skövde, Sweden, September.
14. W. Stokoe, D. Casterline, and C. Croneberg. 1965. A Dictionary of American Sign Language on Linguistic Principles. Gallaudet College Press, Washington D. C., USA.
15. A. Stolcke. 2002. SRILM - an extensible language modeling toolkit. In ICSLP, volume 2, pages 901-904, Denver, CO, September.
16. G. Tsechpenakis, D. Metaxas, and C. Neidle. 2006. Learning-based dynamic coupling of discrete and continuous trackers. Computer Vision and Image Understanding, 104(2-3):140-156, December.
17. C. Valli, editor. 2006. The Gallaudet Dictionary of American Sign Language. Gallaudet U. Press, Washington, DC, USA.
18. C. Vogler and S. Goldenstein. 2007. Facial movement analysis in ASL. Springer Journal on Universal Access in the Information Society, page to appear.
19. C. Vogler and D. Metaxas. 2001. A framework for recognizing the simultaneous aspects of American Sign Language. Computer Vision & Image Understanding, 81(3):358-384, March.
20. C. Vogler and D. Metaxas. 2004. Handshapes and movements: Multiple-channel ASL recognition. Springer Lecture Notes in Artificial Intelligence, (2915): 247-258.
21. R. Yang, S. Sarkar, and B. Loeding. 2007. Enhanced level building algorithm for the movement epenthesis problem in sign language recognition. In Computer Vision and Pattern Recognition.
22. Q. Yuan, S. Sclaroff, and V. Athitsos. 2005. Automatic 2d hand tracking in video sequences. In IEEE Workshop on Applications of Computer Vision.
23. M. Zahedi, D. Keysers, and H. Ney. 2005. Pronunciation clustering and modeling of variability for appearancebased sign language recognition. In International Gesture Workshop 2005, volume 3881, Vannes, France, May.
24. M. Zahedi, P. Dreuw, D. Rybach, T. Deselaers, and H. Ney. 2006. Continuous sign language recognition - approaches from speech recognition and available data resources. In Second Workshop on the Representation and Processing of Sign Languages: Lexicographic Matters and Didactic Scenarios, pages 21-24, Genoa, Italy, May.