Lattice Uncertainty Visualization: Understanding Machine Translation and Speech Recognition

Contributors

Christopher Collins, Gerald Penn, Sheelagh Carpendale

Abstract

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 outputs of language technologies. 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 in cross-lingual instant messaging chat and speech recognition, we show how our visualization uses a hybrid layout along with varying transparency, colour, and size to reveal the various hypotheses considered by the algorithms and help people make better-informed decisions about statistically-derived outputs.

Publications

  • C. Collins, S. Carpendale, and G. Penn, “Visualization of Uncertainty in Lattices to Support Decision-Making,” in Proc. of Eurographics/IEEE VGTC Symposium on Visualization (EuroVis), Norrk√∂ping, Sweden, 2007, pp. 51-58.
    [Bibtex] [PDF] [DOI]
    @InProceedings{COL2007b,
      author =    {Christopher Collins and Sheelagh Carpendale and Gerald Penn},
      title =    {Visualization of Uncertainty in Lattices to Support Decision-Making},
      booktitle =    {Proc. of Eurographics/{IEEE VGTC} Symposium on Visualization (EuroVis)},
      year =   2007,
      pages = {51 - 58},
      address =   {Norrk\"{o}ping, Sweden},
      month =   may,
      publisher =   {Eurographics},
      doi = {10.2312/VisSym/EuroVis07/051-058}
    
    }

The definitive version of the full paper on this project is available from the Eurographics Digital Library.

Media


Acknowledgements

Research

EduApps – Supporting Non-Native English Speakers to Overcome Language Transfer Effects

Metatation: Annotation as Implicit Interaction to Bridge Close and Distant Reading

DataTours: A Data Narratives Framework

Perceptual Biases in Font Size as a Data Encoding

Progressive Learning of Topic Modeling Parameters: A Visual Analytics Framework

Abbreviating Text Labels on Demand

NEREx: Named-Entity Relationship Exploration in Multi-Party Conversations

ConToVi: Multi-Party Conversation Exploration using Topic-Space Views

PhysioEx: Visual Analysis of Physiological Event Streams

Using Visual Analytics of Heart Rate Variation to Aid in Diagnostics

Off-Screen Desktop

PivotSlice

Reading Comprehension on Mobile Devices

#FluxFlow: Visual Analysis of Anomalous Information Spreading on Social Media

Optimizing Hierarchical Visualizations with the Minimum Description Length Principle

Lexichrome

SentimentState: Exploring Sentiment Analysis on Twitter

Facilitating Discourse Analysis with Interactive Visualization

DimpVis

Glidgets

TandemTable

Simple Multi-Touch Toolkit

Exploring Text Entities with Descriptive Non-photorealistic Rendering

Investigating the Semantic Patterns of Passwords

Bubble Sets: Revealing Set Relations with Isocontours over Existing Visualizations

Parallel Tag Clouds to Explore Faceted Text Corpora

VisLink: Revealing Relationships Amongst Visualizations

DocuBurst: Visualizing Document Content using Language Structure

Tabletop Text Entry Techniques

Lattice Uncertainty Visualization: Understanding Machine Translation and Speech Recognition

WordNet Visualization

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