American Sign Language natural language generation and machine translation

Authors:
Matt Huenerfauth
Affiliations:
University of Pennsylvania, Philadelphia, PA
Venue:
ACM SIGACCESS Accessibility and Computing
Year:
2005

Citing 2
Cited 1

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Abstract

Although deaf students in the U.S. and Canada are taught written English, their inability to hear spoken English results in most deaf U.S. high school graduates (18 year olds) reading at a fourth-grade (10 year old) level (Holt, 1991). Unfortunately, many deaf accessibility aids, like television closed captioning or teletype telephones, assume the user has strong English literacy skills. Many deaf people with English reading difficulty are fluent in American Sign Language (ASL); so, an English-to-ASL automated machine translation (MT) system could make information and services accessible when English text captioning is too complex or an interpreter is unavailable.