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This paper describes a method for inferring articulatory parameters from acoustics with a neural network trained on paired acoustic and articulatory data. An x-ray microbeam recorded the vertical movements of the lower lip, tongue tip, and tongue dorsum of three speakers saying the English stop consonants in repeated Ce syllables. A neural network was then(More)
We present a useful method for assessing the quality of a typewritten document image and automatically selecting an optimal restoration method based on that assessment. We use five quality measures that assess the severity of background speckle, touching characters, and broken characters. A linear classifier uses these measures to select a restoration(More)
We describe a system that automatically identifies the script used in documents stored electronically in image form. The system can learn to distinguish any number of scripts. It develops a set of representative symbols (templates) for each script by clustering textual symbols from a set of training documents and representing each cluster by its centroid.(More)
We present a new framework for rapid development of mixed-initiative dialog systems. Using this framework, a developer can author sophisticated dialog systems for multiple channels of interaction by specifying an interaction modality, a rich task hierarchy and task parameters, and domain-specific modules. The framework includes a dialog history that tracks(More)
This paper describes a method for asking statistical questions about a large text corpus. We exemplify the method by addressing the question, "What percentage of Federal Register documents are real documents, of possible interest to a text researcher or analyst?" We estimate an answer to this question by evaluating 200 documents selected from a corpus of(More)
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