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Large Lexicon Project: American Sign Language Video Corpus and Sign Language Indexing/Retrieval Algorithms
 

Summary: Large Lexicon Project: American Sign Language Video Corpus and Sign
Language Indexing/Retrieval Algorithms
Vassilis Athitsos 1 , Carol Neidle 2 , Stan Sclaroff 3 , Joan Nash 2 ,
Alexandra Stefan 1 , Ashwin Thangali 3 , Haijing Wang 1 , and Quan Yuan 3
1 Computer Science and Engineering Department, University of Texas at Arlington, Arlington, TX 76019, USA
2 Linguistics Program, Boston University, Boston, MA 02215, USA
3 Computer Science Department, Boston University, Boston, MA 02215, USA
Abstract
Looking up the meaning of an unknown sign is not nearly so straightforward as looking up a word from a written language in a dictionary.
This paper describes progress in an ongoing project to build a system that helps users look up the meaning of ASL signs. An important
part of the project is building a video database with examples of a large number of signs. So far we have recorded video examples for
almost all of the 3,000 signs contained in the Gallaudet dictionary (and some others not listed there). Locations of hands and the face
have been manually annotated for a large number of videos. Using this data, we have built an application that lets the user submit a video
of a sign as a query, and presents to the user the most similar signs from the system database. System performance has been evaluated
in user­independent experiments with a system vocabulary of 921 signs. For 67% of the test signs, the correct sign is included in the 20
most similar signs retrieved by the system.
1. Introduction
Looking up the meaning of an unknown sign is not nearly
so straightforward as looking up a word from a written lan­
guage in a dictionary. This paper describes progress in an

  

Source: Athitsos, Vassilis - Department of Computer Science and Engineering, University of Texas at Arlington

 

Collections: Computer Technologies and Information Sciences