Creating Conversational Characters Using Question Generation Tools
Citations Over TimeTop 20% of 2012 papers
Abstract
This article describes a new tool for extracting question-answer pairs from text articles, and reports three experiments which investigate how suitable this technique is for supplying knowledge to conversational characters. Experiment 1 demonstrates the feasibility of our method by creating characters for 14 distinct topics and evaluating them using hand-authored questions. Experiment 2 evaluates three of these characters using questions collected from naive participants, showing that the generated characters provide full or partial answers to about half of the questions asked. Experiment 3 adds automatically extracted knowledge to an existing, hand-authored character, demonstrating that augmented characters can answer questions about new topics but with some degradation of the ability to answer questions about topics that the original character was trained to answer. Overall, the results show that question generation is a promising method for creating or augmenting a question answering conversational character using an existing text.
Related Papers
- Evaluating Conversational Characters Created through Question Generation.(2011)
- Generating Responses that Reflect Meta Information in User-Generated Question Answer Pairs(2020)
- → Open-Retrieval Conversational Machine Reading(2021)13 cited
- → Ask to Learn: A Study on Curiosity-driven Question Generation(2020)