Composition of Constraint, Hypothesis and Error Models to improve interaction in Human-Machine Interfaces

摘要

Although there are many tasks where output strings are automatically generated from a set of evidence, they are not perfect and human intervention is often required to correct the result. In this paper we present a generic Symbol Input Interaction Method for Human Machine Interfaces that combines multi-source information: an input Hypothesis Model, an Error Model, a Constraint Model and a user interaction scheme.