Recognition of American Sign Language words with a sensory glove using neural networks and a probabilistic model

Author

Neelesh Sarawate

Abstract

"American Sign Language (ASL) is the primary mode of communication of the deaf people with the hearing world. This thesis presents the design of an ASL word recognition system using a sensory glove which is aimed at providing a platform for communication between the deaf community and the hearing world"--Abstract, page iii.

Department(s)

Mechanical and Aerospace Engineering

Degree Name

M.S. in Mechanical Engineering

Publisher

University of Missouri--Rolla

Publication Date

Fall 2004

Pagination

xii, 101 pages

Note about bibliography

Includes bibliographical references.

Rights

© 2004 Neelesh Sarawate, All rights reserved.

Document Type

Thesis - Citation

File Type

text

Language

English

Subject Headings

Human-computer interaction
Hand -- Movements -- Computer simulation
Neural networks (Computer science)
Deaf -- Means of communication
American Sign Language

Thesis Number

T 8699

Print OCLC #

62338185

Link to Catalog Record

Full-text not available: Request this publication directly from Missouri S&T Library or contact your local library.

Recommended Citation

Sarawate, Neelesh, "Recognition of American Sign Language words with a sensory glove using neural networks and a probabilistic model" (2004). Masters Theses. 5807.
https://scholarsmine.mst.edu/masters_theses/5807