This article summarizes a workshop entitled "Detecting, Repairing, and Preventing Human-Machine Miscommunication," held on 4 August 1996 in Portland, Oregon. The author presents the significant issues raised during the four specific workshop sessions. Research related to achieving robust interaction is an important subarea in AI. Early work concerned the correction of spelling or grammatical errors in a user's utterance so that the system could more easily match them against a fixed linguistic model; work has also been done in the area of speech recognition, attempting to find the best fit of a sound signal to legal sequences of linguistic objects. All these approaches have assumed that the system's model is always correct.

The next portion of the workshop was devoted to different approaches to preventing and repairing miscommunication. These sessions represent a progression between different parts of their discourse Research related to achieving from work that clarifies the model or between the discourse robust interaction is an important problem of miscommunication to model and the domain model. Early work concerned work that describes the strategies The last session was the presentation the correction of spelling or grammatical used to repair miscommunication. I of work involving deployed systems errors in a user's utterance so review the most significant issues using speech as a mode of interaction. The approaches were constrained by their have assumed that the system's model differed in two dimensions: First, experimenters impact on overall system performance is always correct.