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sign language
Background: Prelingually deaf persons usually gain only a rudimentary command of speech and prefer sign language to communicate within the deaf community without the handicap they experience in the hearing world.
      
Method: Data were collected with the help of semi-structured interviews; with the deaf patients these were conducted in German sign language.
      
Due to his deafness Sam never developed vocal language but instead used sign language from the age of four.
      
His tic disorder rapidly accelerated from the age of seven over a six-month period and soon sign language was incorporated into tics as complex "vocal" tics.
      
Bursting out "words"in sign language would also occur in front of people unfamiliar with sign language and often with an obscene content although this was not evident to someone not trained in sign language.
      
Iconicity in American sign language: concrete and metaphorical applications
      
Sign language recognition using model-based tracking and a 3D Hopfield neural network
      
This paper presents a sign language recognition system which consists of three modules: model-based hand tracking, feature extraction, and gesture recognition using a 3D Hopfield neural network (HNN).
      
This paper presents an automatic Australian sign language (Auslan) recognition system, which tracks multiple target objects (the face and hands) throughout an image sequence and extracts features for the recognition of sign phrases.
      
We present an improved anatomically based approach to modeling the human hand for use in the animation of the American Sign Language.
      
We take advantage of several correlations between joint rotations in the hand to reduce the number of degrees of freedom in the model and to provide a?simple, natural, and interactive interface for American Sign Language handshape transcription.
      
Physical exposure of sign language interpreters: baseline measures and reliability analysis
      
Our proposed techniques are validated on three different datasets - Australian sign language, hand-labelled object trajectories from video surveillance footage and real-time tracking data obtained in the laboratory.
      
Linguistic modelling and language-processing technologies for Avatar-based sign language presentation
      
This paper presents research into sign language generation from English text at the University of East Anglia that has involved sign language grammar development to support synthesis and visual realisation of sign language by a virtual human avatar.
      
One strand of research in the ViSiCAST and eSIGN projects has concentrated on the generation in real time of sign language performance by a virtual human (avatar) given a phonetic-level description of the required sign sequence.
      
The utility of the conducted research is illustrated in the context of sign language synthesis by a preliminary consideration of plurality and placement within a grammar for British Sign Language (BSL).
      
For deaf persons to have ready access to information and communication technologies (ICTs), the latter must be usable in sign language (SL), i.e., include interlanguage interfaces.
      
Recent developments in visual sign language recognition
      
Research in the field of sign language recognition has made significant advances in recent years.
      
 

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