Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition
Representing Trees of Higer Degree
WADS '99 Proceedings of the 6th International Workshop on Algorithms and Data Structures
Information Visualization: Perception for Design
Information Visualization: Perception for Design
ACM SIGGRAPH 2005 Papers
An improved error model for noisy channel spelling correction
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Multicriteria Optimization
A Phoneme-Based Student Model for Adaptive Spelling Training
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
Modeling engagement dynamics in spelling learning
AIED'11 Proceedings of the 15th international conference on Artificial intelligence in education
Poisson-based inference for perturbation models in adaptive spelling training
International Journal of Artificial Intelligence in Education
An Effective Conceptual Multisensory Multimedia Model To Support Dyslexic Children In Learning
International Journal of Information and Communication Technology Education
Towards a Framework for Modelling Engagement Dynamics in Multiple Learning Domains
International Journal of Artificial Intelligence in Education - Best of AIED 2011
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We present a novel framework for the multimodal display of words using topological, appearance, and auditory representations. The methods are designed for effective language training and serve as a learning aid for individuals with dyslexia. Our topological code decomposes the word into its syllables and displays it graphically as a tree structure. The appearance code assigns color attributes and shape primitives to each letter and takes into account conditional symbol probabilities, code ambiguities, and phonologically confusable letter combinations. An additional auditory code assigns midi events to each symbol and thus generates a melody for each input string. The entire framework is based on information theory and utilizes a Markovian language model derived from linguistic analysis of language corpora for English, French, and German. For effective word repetition a selection controller adapts to the user's state and optimizes the learning process by minimizing error entropy. The performance of the method was evaluated in a large scale experimental study involving 80 dyslexic and non-dyslexic children. The results show significant improvements in writing skills in both groups after small amounts of daily training. Our approach combines findings from 3D computer graphics, visualization, linguistics, perception, psychology, and information theory.