Abstract
This work presents a pilot study for the application of argument mining techniques in the context of argumentative Dialogue Systems. We extract the argument structure of an online debate and show how it can be utilized to generate artificial persuasive dialogues in an agent-agent scenario. The interaction between the agents is formalized as argument game and the resulting artificial dialogues are evaluated in a user study by comparing them to human generated ones. The outcomes indicate that the artificial dialogues are logically consistent and thus show that the use of the employed argument annotation scheme was successful.
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https://idebate.org/debatabase (last accessed 16 March 2019).
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Material reproduced from www.iedebate.org with the permission of the International Debating Education Association. Copyright ©2005 International Debate Education Association. All Rights Reserved.
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Material reproduced from www.iedebate.org with the permission of the International Debating Education Association. Copyright ©2005 International Debate Education Association. All Rights Reserved.
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https://marketplace.clickworker.com (last accessed 16 March 2019).
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Acknowledgements
This work has been funded by the Deutsche Forschungsgemeinschaft (DFG) within the project “How to Win Arguments—Empowering Virtual Agents to Improve their Persuasiveness”, Grant Number 376696351, as part of the Priority Program “Robust Argumentation Machines (RATIO)” (SPP-1999).
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Rach, N., Langhammer, S., Minker, W., Ultes, S. (2019). Utilizing Argument Mining Techniques for Argumentative Dialogue Systems. In: D'Haro, L., Banchs, R., Li, H. (eds) 9th International Workshop on Spoken Dialogue System Technology. Lecture Notes in Electrical Engineering, vol 579. Springer, Singapore. https://doi.org/10.1007/978-981-13-9443-0_12
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