Using Alignments in Automatic Paraphrase Production to Combat Data Sparsity in Question Interpretation for a Virtual Patient Dialogue System
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Date
2019-05
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The Ohio State University
Abstract
Automatic paraphrase generation is a task explored in many areas of natural language processing. In this study we attempt to use automatic paraphrasing to augment the training data for a virtual patient dialogue system. The system performs in-domain question answering in an attempt to replicate the function of standardized patients, and aid medical students in practicing their patient interviewing skills.
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Keywords
Natural Language Processing, Paraphrase Generation, Virtual Dialogue System, Virtual Patient, Patient Interview