Chandler: An Explainable Sarcastic Response Generator

Silviu Oprea, Steven Wilson, Walid Magdy
2021 Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations   unpublished
We introduce Chandler, a system that generates sarcastic responses to a given utterance. Previous sarcasm generators assume the intended meaning that sarcasm conceals is the opposite of the literal meaning. We argue that this traditional theory of sarcasm provides a grounding that is neither necessary, nor sufficient, for sarcasm to occur. Instead, we ground our generation process on a formal theory that specifies conditions that unambiguously differentiate sarcasm from non-sarcasm.
more » ... Chandler not only generates sarcastic responses, but also explanations for why each response is sarcastic. This provides accountability, crucial for avoiding miscommunication between humans and conversational agents, particularly considering that sarcastic communication can be offensive. In human evaluation, Chandler achieves comparable or higher sarcasm scores, compared to state-of-the-art generators, while generating more diverse responses, that are more specific and more coherent to the input.
doi:10.18653/v1/2021.emnlp-demo.38 fatcat:7lcnmhei3zg37lyippdwl4uxha