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Abstract or Description
It is difficult to build applications that effectively use recognizers, in part because of lack of toolkit-level support for dealing with recognition errors. This dissertation presents an architecture that addresses that problem.
Recognition technologies such as speech, gesture, and handwriting recognition, have made great strides in recent years. By providing support for more natural forms of communication, recognition can make computers more accessible. Such “natural” interfaces are particularly useful in settings where a keyboard and mouse are not available, as in very large or very small displays, and in mobile and ubiquitous computing. However, recognizers are error-prone: they may not interpret input as the user intended. This can confuse the user, cause performance problems, and result in brittle interaction dialogues.