  In this paper, a novel approach to sign language recognition based on state
tying in each of data streams is presented. In this framework, it is assumed
that hand gesture signal is represented in terms of six synchronous data
streams, i.e., the left/right hand position, left/right hand orientation and
left/right handshape. This approach offers a very accurate representation of
the sign space and keeps the number of parameters reasonably small in favor of
a fast decoding. Experiments were carried out for 5177 Chinese signs. The real
time isolated recognition rate is 94.8%. For continuous sign recognition, the
word correct rate is 91.4%. Keywords: Sign language recognition; Automatic sign
language translation; Hand gesture recognition; Hidden Markov models;
State-tying; Multimodal user interface; Virtual reality; Man-machine systems.
