학술논문

Beyond Words: Multi-modal Chat Summarization using Text with Emoji and GIF Emotion Analysis
Document Type
Conference
Source
2024 International Conference on Intelligent Systems and Advanced Applications (ICISAA) Intelligent Systems and Advanced Applications (ICISAA), 2024 International Conference on. :1-6 Oct, 2024
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Engineering Profession
Power, Energy and Industry Applications
Robotics and Control Systems
Visualization
Emotion recognition
Analytical models
Text recognition
Oral communication
Transformers
Digital communication
Intelligent systems
Emojis
Chat Summarization
Multimodal Communication
Emotion Detection
Emoji Sentiment Analysis
GIF Emotion Recognition
Transformer Models
Language
Abstract
This paper presents a novel approach that signifies a methodological change in the way that a conversation is summarized in a chat. The term “Beyond Words” implies that the chat summarization process transcends conventional text-based techniques. It suggests that in addition to the textual content, the summarization takes into account extra elements like the emotions conveyed by emojis and GIFs. “Beyond Words” highlights a more thorough and inclusive method of summarizing chats by considering visual cues like emojis and GIFs that enhance communication in addition to written text. Our methodology aims to provide a more comprehensive and expressive representation of conversations by integrating these multimodal components. The paper describes the development and fine-tuning of transformer model using available familiar datasets. Furthermore, incorporating emotion detection from GIFs using a fine-tuned CNN pre-trained model, as well as emotion analysis of chat emojis, improve the summarization process. The results show that our approach is effective at capturing the essence of conversations, including not only words but also the emotive and visual dimensions inherent in modern digital communication. This project presents a fresh approach to chat summarization, allowing users to understand lengthy conversations in a clear and informative format.