The visual display of quantitative information
The visual display of quantitative information
High-speed visual estimation using preattentive processing
ACM Transactions on Computer-Human Interaction (TOCHI)
Statistical methods for speech recognition
Statistical methods for speech recognition
Multimodal error correction for speech user interfaces
ACM Transactions on Computer-Human Interaction (TOCHI)
Investigating human-computer optimization
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Visualizing Knowledge about Virtual Reconstructions of Ancient Architecture
CGI '99 Proceedings of the International Conference on Computer Graphics
INFOVIS '01 Proceedings of the IEEE Symposium on Information Visualization 2001 (INFOVIS'01)
A Next Step: Visualizing Errors and Uncertainty
IEEE Computer Graphics and Applications
Information Visualization: Perception for Design
Information Visualization: Perception for Design
BEST PAPER: A Knowledge Task-Based Framework for Design and Evaluation of Information Visualizations
INFOVIS '04 Proceedings of the IEEE Symposium on Information Visualization
Semiology of graphics
Effects of machine translation on collaborative work
CSCW '06 Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work
Word graph based speech rcognition error correction by handwriting input
Proceedings of the 8th international conference on Multimodal interfaces
Language Networks on LiveJournal
HICSS '07 Proceedings of the 40th Annual Hawaii International Conference on System Sciences
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Lattice graphs are used as underlying data structures in many statistical processing systems, including natural language processing. Lattices compactly represent multiple possible outputs and are usually hidden from users. We present a novel visualization intended to reveal the uncertainty and variability inherent in statistically-derived lattice structures. Applications such as machine translation and automated speech recognition typically present users with a best-guess about the appropriate output, with apparent complete confidence. Through case studies we show how our visualization uses a hybrid layout along with varying transparency, colour, and size to reveal the lattice structure, expose the inherent uncertainty in statistical processing, and help users make better-informed decisions about statistically-derived outputs.