Learning the basic units in American sign language using discriminative segmental feature selection

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn , Issue , 2009, Pages 4757-4760

  Yin, Pei ^a   Starner, Thad ^a   Hamilton, Harley ^a   Essa, Irfan ^a   Rehg, James M ^a  

^a Georgia Institute of Technology   (United States)

Author keywords

American sign language; Feature selection; Machine learning

Indexed keywords

AMERICAN SIGN LANGUAGE; DATA-DRIVEN; DISCRIMINATIVE FEATURES; FEATURE SELECTION; HUMAN PERCEPTION; INTERNAL STRUCTURE; MACHINE LEARNING; MACHINE PERCEPTION; NATURAL LANGUAGES; REDUCED MODEL; SPOKEN LANGUAGES; TEMPORAL SEGMENTS;

ACOUSTICS; EDUCATION; QUERY LANGUAGES; ROBOT LEARNING; SIGNAL PROCESSING;

LINGUISTICS;

EID: 70349204647     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2009.4960694     Document Type: Conference Paper

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