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CVPR
2012
IEEE
11 years 7 months ago
Enhanced continuous sign language recognition using PCA and neural network features
In this work a Gaussian Hidden Markov Model (GHMM) based automatic sign language recognition system is built on the SIGNUM database. The system is trained on appearance-based feat...
Yannick L. Gweth, Christian Plahl, Hermann Ney
PAMI
1998
193views more  PAMI 1998»
13 years 4 months ago
Real-Time American Sign Language Recognition Using Desk and Wearable Computer Based Video
—We present two real-time hidden Markov model-based systems for recognizing sentence-level continuous American Sign Language (ASL) using a single camera to track the user’s una...
Thad Starner, Joshua Weaver, Alex Pentland
ICPR
2006
IEEE
14 years 6 months ago
Detecting Coarticulation in Sign Language using Conditional Random Fields
Coarticulation is one of the important factors that makes automatic sign language recognition a hard problem. Unlike in speech recognition, coarticulation effects in sign language...
Ruiduo Yang, Sudeep Sarkar
ICPR
2008
IEEE
14 years 6 months ago
Automatic generation of HMM topology for sign language recognition
Sign language is used for communicating to people with hearing difficulties. Recogntion of a sign language image sequence is challenging because of the variety of hand shapes and ...
Tadashi Matsuo, Yoshiaki Shirai, Nobutaka Shimada
FCCM
2002
IEEE
114views VLSI» more  FCCM 2002»
13 years 10 months ago
Implementing a Simple Continuous Speech Recognition System on an FPGA
Speech recognition is a computationally demanding task, particularly the stage which uses Viterbi decoding for converting pre-processed speech data into words or sub-word units. W...
Stephen J. Melnikoff, Steven F. Quigley, Martin J....