对话内容常常围绕主题展开。
- 医疗领域对话摘要:
- 法律领域对话摘要:
- How to Interact and Change? Abstractive Dialogue Summarization with Dialogue Act Weight and Topic Change Info
- Improving Abstractive Dialogue Summarization with Hierarchical Pretraining and Topic Segment
- Topic-Aware Contrastive Learning for Abstractive Dialogue Summarization
- Unsupervised Summarization for Chat Logs with Topic-Oriented Ranking and Context-Aware Auto-Encoders
- Multi-View Sequence-to-Sequence Models with Conversational Structure for Abstractive Dialogue Summarization
- Topic-Oriented Spoken Dialogue Summarization for Customer Service with Saliency-Aware Topic Modeling
- Extracting Decisions from Multi-Party Dialogue Using Directed Graphical Models and Semantic Similarity
- Automatic analysis of multiparty meetings
- Improving Abstractive Dialogue Summarization with Graph Structures and Topic Words
- A Finer-grain Universal Dialogue Semantic Structures based Model For Abstractive Dialogue Summarization
- Situation-Based Multiparticipant Chat Summarization: a Concept, an Exploration-Annotation Tool and an Example Collection
- Other Roles Matter! Enhancing Role-Oriented Dialogue Summarization via Role Interactions
- Summ^N: A Multi-Stage Summarization Framework for Long Input Dialogues and Documents
- Dialogue Summaries as Dialogue States (DS2), Template-Guided Summarization for Few-shot Dialogue State Tracking
- DialogLM: Pre-Trained Model for Long Dialogue Understanding and Summarization
- A Survey on Dialogue Summarization: Recent Advances and New Frontiers:2022年综述
- CONFIT: Toward Faithful Dialogue Summarization with Linguistically-Informed Contrastive Fine-tuning
- Domain-Oriented Prefix-Tuning: Towards Efficient and Generalizable Fine-tuning for Zero-Shot Dialogue Summarization
- From spoken dialogue to formal summary: An utterance rewriting for dialogue summarization:还没有发出来
- TANet: Thread-Aware Pretraining for Abstractive Conversational Summarization
- (2021 SIGIR 美团) Distant Supervision based Machine Reading Comprehension for Extractive Summarization in Customer Service
美团官方讲解博文:对话摘要技术在美团的探索(SIGIR) - 会议摘要
- 对话摘要指标评估:DialSummEval: Revisiting Summarization Evaluation for Dialogues
证明对话摘要任务适宜于生成式摘要而非抽取式摘要:Topic-aware Pointer-Generator Networks for Summarizing Spoken Conversations 一文的摘要。
重要公开数据集:
- AMI Meeting Corpus(dialogue acts, topic descriptions, named entities, hand gestures, and gaze direction都是标注好的)
官网:AMI Corpus - Annotation
使用这一数据集的论文:
Automatic analysis of multiparty meetings - SamSum
使用这一数据集的论文:
Multi-View Sequence-to-Sequence Models with Conversational Structure for Abstractive Dialogue Summarization - 其他整理数据集的项目:
重要术语:dialogue act https://en.wikipedia.org/wiki/Dialog_act
代表重要外部信息的interactive pattern,the effect of an utterance on the context,includes some conversational interactions and provides important information to understand dialogue
使用这一概念的论文:
How to Interact and Change? Abstractive Dialogue Summarization with Dialogue Act Weight and Topic Change Info
Extracting Decisions from Multi-Party Dialogue Using Directed Graphical Models and Semantic Similarity
Unsupervised Modeling of Twitter Conversations
其他整理会议/对话摘要论文的工作: