Corpus 3D Natural Movements and Sign Language Primitives of Movement
Proceedings of the International Gesture Workshop on Gesture and Sign Language in Human-Computer Interaction
ARGo: An Architecture for Sign Language Recognition and Interpretation
Proceedings of Gesture Workshop on Progress in Gestural Interaction
A Real-Time Continuous Gesture Recognition System for Sign Language
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
ASL Recognition Based on a Coupling Between HMMs and 3D Motion Analysis
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Immersive VR for Scientific Visualization: A Progress Report
IEEE Computer Graphics and Applications
Vision-Based Gesture Recognition: A Review
GW '99 Proceedings of the International Gesture Workshop on Gesture-Based Communication in Human-Computer Interaction
Stimulating Research into Gestural Human Machine Interaction
GW '99 Proceedings of the International Gesture Workshop on Gesture-Based Communication in Human-Computer Interaction
Research on Computer Science and Sign Language: Ethical Aspects
GW '01 Revised Papers from the International Gesture Workshop on Gesture and Sign Languages in Human-Computer Interaction
A Real-Time Large Vocabulary Recognition System for Chinese Sign Language
GW '01 Revised Papers from the International Gesture Workshop on Gesture and Sign Languages in Human-Computer Interaction
Towards an Automatic Sign Language Recognition System Using Subunits
GW '01 Revised Papers from the International Gesture Workshop on Gesture and Sign Languages in Human-Computer Interaction
Signer-Independent Continuous Sign Language Recognition Based on SRN/HMM
GW '01 Revised Papers from the International Gesture Workshop on Gesture and Sign Languages in Human-Computer Interaction
A Real-Time Large Vocabulary Continuous Recognition System for Chinese Sign Language
PCM '01 Proceedings of the Second IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Multimodal interface for human-machine communication
Large vocabulary sign language recognition based on hierarchical decision trees
Proceedings of the 5th international conference on Multimodal interfaces
Error-Tolerant Sign Retrieval Using Visual Features and Maximum A Posteriori Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A vision-based sign language recognition system using tied-mixture density HMM
Proceedings of the 6th international conference on Multimodal interfaces
Multilayer architecture in sign language recognition system
Proceedings of the 6th international conference on Multimodal interfaces
Gesture-driven American sign language phraselator
ICMI '05 Proceedings of the 7th international conference on Multimodal interfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Improving the efficacy of automated sign language practice tools
ACM SIGACCESS Accessibility and Computing - ASSETS 2007 doctoral consortium
Signing Exact English (SEE): Modeling and recognition
Pattern Recognition
Signing Exact English (SEE): Modeling and recognition
Pattern Recognition
Effort analysis in signer-independent sign gestures
Journal of Experimental & Theoretical Artificial Intelligence
Modelling and segmenting subunits for sign language recognition based on hand motion analysis
Pattern Recognition Letters
A study of sign language coarticulation
ACM SIGACCESS Accessibility and Computing
A Chinese sign language recognition system based on SOFM/SRN/HMM
Pattern Recognition
Signer adaptation based on etyma for large vocabulary Chinese sign language recognition
PCM'07 Proceedings of the multimedia 8th Pacific Rim conference on Advances in multimedia information processing
Gesture recognition for fingerspelling applications: an approach based on sign language cheremes
Proceedings of the 12th international ACM SIGACCESS conference on Computers and accessibility
A new instrumented approach for translating American sign language into sound and text
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Using signing space as a representation for sign language processing
GW'05 Proceedings of the 6th international conference on Gesture in Human-Computer Interaction and Simulation
Re-sampling for chinese sign language recognition
GW'05 Proceedings of the 6th international conference on Gesture in Human-Computer Interaction and Simulation
Static gesture quantization and DCT based sign language generation
ACII'05 Proceedings of the First international conference on Affective Computing and Intelligent Interaction
Design and evaluation of classifier for identifying sign language videos in video sharing sites
Proceedings of the 14th international ACM SIGACCESS conference on Computers and accessibility
Identifying Sign Language Videos in Video Sharing Sites
ACM Transactions on Accessible Computing (TACCESS)
Hidden Markov model for human to computer interaction: a study on human hand gesture recognition
Artificial Intelligence Review
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In this paper we present a novel approach to continuous, whole-sentence ASL recognition that uses phonemes instead of whole signs as the basic units. Our approach is based on a sequential phonological model of ASL. According to this model the ASL signs can be broken into movements and holds, which are both considered phonemes.This model does away with the distinction between whole signs and epenthesis movements that we made in previous work [17]. Instead, epenthesis movements are just like the other movements that constitute the signs.We subsequently train Hidden Markov Models (HMMs) to recognize the phonemes, instead of whole signs and epenthesis movements that we recognized previously [17]. Because the number of phonemes is limited, HMM-based training and recognition of the ASL signal becomes computationally more tractable and has the potential to lead to the recognition of large-scale vocabularies.We experimented with a 22 word vocabulary, and we achieved similar recognition rates with phoneme-and word-based approaches. This result is very promising for scaling the task in the future.