Fully Automated Generation of Question-Answer Pairs for Scripted Virtual Instruction
We introduce a novel approach for automatically generating a virtual instructor from textual input only. Our fully implemented system first analyzes the rhetorical structure of the input text and then creates various question-answer pairs using patterns. These patterns have been derived from correlations found between rhetorical structure of monologue texts and question-answer pairs in the corresponding dialogues. A selection of the candidate pairs is verbalized into a diverse collection of question-answer pairs. Finally the system compiles the collection of question-answer pairs into scripts for a virtual instructor. Our end-to-end system presents questions in pre-fixed order and the agent answers them. Our system was evaluated with a group of twenty-four subjects. The evaluation was conducted using three informed consent documents of clinical trials from the domain of colon cancer. Each of the documents was explained by a virtual instructor using 1) text, 2) text and agent monologue, and 3) text and agent performing question-answering. Results show that an agent explaining an informed consent document did not provide significantly better comprehension scores, but did score higher on satisfaction, compared to two control conditions.
KeywordsDialogue Generation Rhetorical Structure Theory Medical Documents
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