Introduction to algorithms
Communications of the ACM
Fundamentals of speech recognition
Fundamentals of speech recognition
A tool for the rapid evaluation of input devices using Fitts' law models
ACM SIGCHI Bulletin
Error-Tolerant Retrieval of Trees
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-Time American Sign Language Recognition Using Desk and Wearable Computer Based Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
A framework for recognizing the simultaneous aspects of American sign language
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
Handbook of Algorithms
Modern Information Retrieval
The Reactive Keyboard
Teaching Communication Skills to Hearing-Impaired Children
IEEE MultiMedia
Toward Scalability in ASL Recognition: Breaking Down Signs into Phonemes
GW '99 Proceedings of the International Gesture Workshop on Gesture-Based Communication in Human-Computer Interaction
Finite-state transducers in language and speech processing
Computational Linguistics
Pattern Recognition, Third Edition
Pattern Recognition, Third Edition
Retrieval by shape similarity with perceptual distance andeffective indexing
IEEE Transactions on Multimedia
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image and video for hearing impaired people
Journal on Image and Video Processing
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Abstract--This paper proposes an efficient error-tolerant approach to retrieving sign words from a Taiwanese Sign Language (TSL) database. This database is tagged with visual gesture features and organized as a multilist code tree. These features are defined in terms of the visual characteristics of sign gestures by which they are indexed for sign retrieval and displayed using an anthropomorphic interface. The maximum a posteriori estimation is exploited to retrieve the most likely sign word given the input feature sequence. An error-tolerant mechanism based on mutual information criterion is proposed to retrieve a sign word of interest efficiently and robustly. A user-friendly anthropomorphic interface is also developed to assist learning TSL. Several experiments were performed in an educational environment to investigate the system's retrieval accuracy. Our proposed approach outperformed a dynamic programming algorithm in its task and shows tolerance to user input errors.