Conversational Summarization Task
A Conversational Summarization Task is a text summarization task whose source inputs are conversation records.
- Context:
- It (often) involves creating a shorter version of a long conversation which retains the essential information and context.
- ...
- Example(s):
- Counter-Example(s):
- See: Conversational Summarization Evaluation, Natural Language Processing, Automatic Summarization, Machine Learning.
References
2024
- (GM-RKB ChatGPT, 2024) ⇒ Prompt: Summarize the concept Conversational Summarization Task in 1-2 paragraphs. GM-RKB ChatGPT (model: gpt-4-1106-preview). Retrieved: 2024-01-21.
- QUOTE: The Conversational Summarization Task is concerned with creating concise, coherent summaries of conversations. Unlike traditional document summarization, this task deals with the dynamic and sometimes informal structure of dialogue, which includes multiple speakers, interruptions, and colloquial language. The goal is to capture the key points, decisions, action items, and topics discussed within a conversation, whether it is a face-to-face dialogue, a telephone call, or an online chat session.
In performing conversational summarization, algorithms and systems focus on understanding the context, speaker intents, relationships between utterances, and the evolution of the discussion over time. This requires advanced natural language processing techniques that can handle the nuances of spoken language, such as disfluencies, non-standard grammar, and the use of fillers. Both extractive and abstractive approaches are explored, with the former selecting important sentences directly from the conversation, and the latter generating new sentences that encapsulate the essence of the discussion. Practical applications include providing meeting summaries, assisting with customer service records, and improving accessibility for those who are deaf or hard of hearing by offering succinct written versions of spoken interactions.
- QUOTE: The Conversational Summarization Task is concerned with creating concise, coherent summaries of conversations. Unlike traditional document summarization, this task deals with the dynamic and sometimes informal structure of dialogue, which includes multiple speakers, interruptions, and colloquial language. The goal is to capture the key points, decisions, action items, and topics discussed within a conversation, whether it is a face-to-face dialogue, a telephone call, or an online chat session.
2023
- (Manuvinakurike et al., 2023) ⇒ Ramesh Manuvinakurike, Saurav Sahay, Sangeeta Manepalli, and Lama Nachman. (2023). “Zero-Shot Conversational Summarization Evaluations with Small Large Language Models.” doi:10.48550/arXiv.2311.18041