Well, Now We Know! Unveiling Sarcasm: Initiating and Exploring Multimodal Conversations with Reasoning
Gopendra Vikram Singh, Mauajama Firdaus, Dushyant Singh Chauhan, Asif Ekbal, Pushpak Bhattacharyya
Abstract
Sarcasm is a widespread linguistic phenomenon that poses a considerable challenge to explain due to its subjective nature, absence of contextual cues and rooted personal perspectives. Even though the identification of sarcasm has been extensively studied in dialogue analysis, merely detecting sarcasm falls short of enabling conversational systems to genuinely comprehend the underlying meaning of a conversation and generate fitting responses. It is imperative to not only detect sarcasm but also pinpoint its origination and the rationale behind the sarcastic expressions to capture its authentic essence. In this paper, we delve into the discourse structure of conversations infused with sarcasm and introduce a novel task -Sarcasm Initiation and Reasoning in Conversations (SIRC). Embedded in a multimodal environment and involving a combination of both English and code-mixed interactions, the objective of the task is to discern the trigger or starting point of sarcasm. Additionally, the task involves producing a natural language explanation that rationalizes the satirical dialogues. To achieve this, we introduce Sarcasm Initiation and Reasoning Dataset (SIRD) to facilitate our task and provide sarcasm initiation annotations and reasoning. We develop a comprehensive model named Sarcasm Initiation and Reasoning Generation (SIRG), which is designed to encompass textual, audio, and visual representations. To achieve this, we introduce a unique shared fusion method that employs cross-attention mechanisms to seamlessly integrate these diverse modalities. Our experimental outcomes, conducted on the SIRD dataset, demonstrate that our proposed framework establishes a new benchmark for both sarcasm initiation and its reasoning generation in the context of multimodal conversations. The code and dataset can be accessed from https://www.iitp.ac.in/ ∼ ai-nlp-ml/resources. html#sarcasm-explain and https://github.com/GussailRaat/ SIRG-Sarcasm-Initiation-and-Reasoning-Generation.
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Builds on5
- Multi-Modal Sarcasm Detection via Cross-Modal Graph Convolutional NetworkBin Liang, Chenwei Lou, Xiang Li, Min Yang et al.ACL 2022 · 151 citations
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