Using Language Groundings for Context-Sensitive Text Prediction
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Type of Work5 PAGES
conference papers and proceedings preprints
Citation of Original PublicationTimothy Lewis, Amy Hurst, Matthew E. Taylor, & Cynthia Matuszek, Using Language Groundings for Context-Sensitive Text Prediction, EMNLP Workshop on Uphill Battles in Language Processing: Scaling Early Achievements to Robust Methods, 2016;
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context sensitive generation
Interactive Robotics and Language Lab
In this paper, we present the concept of using language groundings for context sensitive text prediction using a semantically informed, context-aware language model. We show initial findings from a preliminary study investigating how users react to a communication interface driven by context-based prediction using a simple language model. We suggest that the results support further exploration using a more informed semantic model and more realistic context.