Automatic Sign Language Analysis: A Survey and the Future beyond Lexical Meaning
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognition of sign language subwords based on boosted hidden Markov models
ICMI '05 Proceedings of the 7th international conference on Multimodal interfaces
Effort analysis in signer-independent sign gestures
Journal of Experimental & Theoretical Artificial Intelligence
Towards automated large vocabulary gesture search
Proceedings of the 2nd International Conference on PErvasive Technologies Related to Assistive Environments
A Similarity Measure for Vision-Based Sign Recognition
UAHCI '09 Proceedings of the 5th International Conference on Universal Access in Human-Computer Interaction. Part III: Applications and Services
Proceedings of the 11th international ACM SIGACCESS conference on Computers and accessibility
A framework for continuous multimodal sign language recognition
Proceedings of the 2009 international conference on Multimodal interfaces
A Chinese sign language recognition system based on SOFM/SRN/HMM
Pattern Recognition
Accurate and Accessible Motion-Capture Glove Calibration for Sign Language Data Collection
ACM Transactions on Accessible Computing (TACCESS)
A database-based framework for gesture recognition
Personal and Ubiquitous Computing
Recognition of dynamic gestures in arabic sign language using two stages hierarchical scheme
International Journal of Knowledge-based and Intelligent Engineering Systems
Automatic recognition of sign language subwords based on portable accelerometer and EMG sensors
International Conference on Multimodal Interfaces and the Workshop on Machine Learning for Multimodal Interaction
Features extraction from hand images based on new detection operators
Pattern Recognition
A comparison between etymon- and word-based chinese sign language recognition systems
GW'05 Proceedings of the 6th international conference on Gesture in Human-Computer Interaction and Simulation
3D articulated hand tracking based on behavioral model
Transactions on Edutainment VIII
Finding recurrent patterns from continuous sign language sentences for automated extraction of signs
The Journal of Machine Learning Research
Non-manual cues in automatic sign language recognition
Personal and Ubiquitous Computing
Collecting and evaluating the CUNY ASL corpus for research on American Sign Language animation
Computer Speech and Language
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Hitherto, the major challenge to sign language recognition is how to develop approaches that scale well with increasing vocabulary size. In this paper we present an approach to large vocabulary, continuous Chinese Sign Language (CSL) recognition that uses phonemes instead of whole signs as the basic units. Since the number of phonemes is limited, HMM-based training and recognition of the CSL signal becomes more tractable and has the potential to recognize enlarged vocabularies. Furthermore, the proposed method facilitates the CSL recognition when finger-alphabet is blended with gestures. About 2400 phonemes are defined for CSL. One HMM is built for each phoneme, and then the signs are encoded based on these phonemes. A decoder that uses tree-structured network is presented. Clustering of the Gaussians on the states, Language model and N-best-pass is used to improve the performance of the system. Experiments on a 5119 sign vocabulary are carried out, and the result is exciting.