There now exist direct route connectionist models of reading aloud (i.e. text to phoneme conversion) that learn to perform on their training data and unseen words with accuracy comparable to that of humans. They also exhibit a number of developmental, reaction time and brain damage effects that are observed experimentally. However, various deficiencies (such as their failure to perform accurate...

This chapter describes learning techniques that are the basis of a "visual speech recognition" or "lipreading" system 1 • Model-based vision systems currently have the best performance for many visual recognition tasks. For geometrically simple domains, models can sometimes be constructed by hand using CAD-like tools. Such models are difficult and expensive to construct, however, and are inadeq...

With the tremendous increase in the amount of biological literature, developing automated methods for extracting big data from papers, building models and explaining big mechanisms becomes a necessity. We describe here our approach to translating machine reading outputs, obtained by reading biological signaling literature, to discrete models of cellular networks. We use outputs from three diffe...

Reading in many alphabetic writing systems depends on both item-specific knowledge used to read irregular words (sew, yacht) and generative spelling-sound knowledge used to read pseudowords (tew, yash). Research into the neural basis of these abilities has been directed largely by cognitive accounts proposed by the dual-route cascaded and triangle models of reading. We develop a framework that ...

Reading proficiency is a fundamental component of language competency. However, finding topical texts at an appropriate reading level for foreign and second language learners is a challenge for teachers. This task can be addressed with natural language processing technology to assess reading level. Existing measures of reading level are not well suited to this task, but previous work and our ow...