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Question Response Dialog Systems (QA) are useful in a wide range of contexts in which the primary role of a virtual character represents the answering of the human user's questions. In QA-based dialog systems, the primary interpretation task may be voted as the issue of a user with a question expected from the content author. This project examines for the first time, as methods for automatic paraphrasing, the authors can support the authors in determining a large number of expected question variants, which can drastically increase the interpretation of the interpretation of robustness both for the chatted and spoken language. By evaluating the project with an existing virtual patient's virtual patient and the new Virtual Guide for Columbus, the Ohio Science Museum (Center of Science and Industry), the project will improve the medical education and an inspiring science example in action for the children who Participate the museum. It also promises to improve the effectiveness of short investment rating in educational software and commercial QA systems for frequently asked questions.
The proposed approach is the first to examine the potential of advanced automatic paraphrase techniques to improve the robustness of the interpretation in an easy-to-be eruded QA dialog system. Through the use of paraphrasing in content accessories, it becomes possible to use the author's knowledge of the space of functional issues, which may result in dramatic improvements in interpretation accuracy; This makes it possible to install an effective, task-relevant discrimination room for automatic speech recognition (ASR) -anraining. In order to produce paraphrases, the project uses the grammatical Surface Realizer OpenCCG for lexico syntactic change components together with wide cover resources, vector space models of Word meaning and multiword orientations. To form discriminating ASR models that make a difference in terms of interpretation, paraphrases are incorporated into the semantic error rate estimation. With the help of data collected by medical students and museum visitors, the project assesses the approach due to impact on interpretation accuracy and qualitative uses.