Collecting a motion-capture corpus of American Sign Language for data-driven generation research

  • Authors:
  • Pengfei Lu;Matt Huenerfauth

  • Affiliations:
  • City University of New York (CUNY), New York, NY;City University of New York (CUNY), Flushing, NY

  • Venue:
  • SLPAT '10 Proceedings of the NAACL HLT 2010 Workshop on Speech and Language Processing for Assistive Technologies
  • Year:
  • 2010

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Abstract

American Sign Language (ASL) generation software can improve the accessibility of information and services for deaf individuals with low English literacy. The understand-ability of current ASL systems is limited; they have been constructed without the benefit of annotated ASL corpora that encode detailed human movement. We discuss how linguistic challenges in ASL generation can be addressed in a data-driven manner, and we describe our current work on collecting a motion-capture corpus. To evaluate the quality of our motion-capture configuration, calibration, and recording protocol, we conducted an evaluation study with native ASL signers.