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ABSTRACT

Interfaces based on recognition technologies are used extensively in both the commercial and research worlds. But recognizers are still error-prone, and this results in human performance problems, brittle dialogues, and other barriers to acceptance and utility of recognition systems. Interface techniques specialized to recognition systems can help reduce the burden of recognition errors, but building these interfaces depends on knowledge about the ambiguity inherent in recognition. We have extended a user interface toolkit in order to model and to provide structured support for ambiguity at the input event level. This makes it possible to build re-usable interface components for resolving ambiguity and dealing with recognition errors. These interfaces can help to reduce the negative effects of recognition errors. By providing these components at a toolkit level, we make it easier for application writers to provide good support for error handling. Further, with this robust support, we are able to explore new types of interfaces for resolving a more varied range of ambiguity.

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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)

Additional Classification:
  H. Information Systems
  H.1 MODELS AND PRINCIPLES

  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.0 General
          Subjects: Cognitive simulation
      I.2.7 Natural Language Processing
          Subjects: Speech recognition and synthesis

General Terms:
Design, Human Factors, Languages, Management, Performance, Reliability, Theory

Keywords:
ambiguous input, input models, interaction techniques, pen-based interfaces, recognition errors, recognition-based interfaces, speech recognition, toolkits