Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)

Sign Language Keyword Extraction based on GLOSS

Authors
Ruizhu Wu
Corresponding Author
Ruizhu Wu
Available Online April 2019.
DOI
https://doi.org/10.2991/icmeit-19.2019.51How to use a DOI?
Keywords
Gloss; sign language; keyword extraction; Word2vec.
Abstract
In order to quickly understand the content of sign language video, the theme of handshake language, and facilitate the efficient management and retrieval of sign language corpus, the annotation corpus in the parallel corpus of the text first maps all words to one using the word2vec model based on deep learning tools. Abstract word vector space; then word clustering based on K-means algorithm to achieve keyword extraction. Experiments show that the algorithm has better keyword extraction effect for sign language videos with more keywords and longer video time.
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Proceedings
3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)
Part of series
Advances in Computer Science Research
Publication Date
April 2019
ISBN
978-94-6252-708-9
ISSN
2352-538X
DOI
https://doi.org/10.2991/icmeit-19.2019.51How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Ruizhu Wu
PY  - 2019/04
DA  - 2019/04
TI  - Sign Language Keyword Extraction based on GLOSS
BT  - 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmeit-19.2019.51
DO  - https://doi.org/10.2991/icmeit-19.2019.51
ID  - Wu2019/04
ER  -