论文标题
销售电话的端到端对话摘要系统
An End-to-End Dialogue Summarization System for Sales Calls
论文作者
论文摘要
总结销售电话是销售人员手动执行的常规任务。我们提出了一个生产系统，该系统将生成模型与客户代理设置进行了微调，并具有人为的用户体验，以进行交互式摘要策划过程。我们在现实世界中解决对话摘要任务的具有挑战性的方面，包括长输入对话，内容验证，缺乏标记的数据和质量评估。我们展示了如何将GPT-3作为离线数据标签的利用，以处理培训数据稀缺并在工业环境中适应隐私限制。实验显示了我们的模型在解决公共数据集上的汇总和内容验证任务方面的重大改进。
Summarizing sales calls is a routine task performed manually by salespeople. We present a production system which combines generative models fine-tuned for customer-agent setting, with a human-in-the-loop user experience for an interactive summary curation process. We address challenging aspects of dialogue summarization task in a real-world setting including long input dialogues, content validation, lack of labeled data and quality evaluation. We show how GPT-3 can be leveraged as an offline data labeler to handle training data scarcity and accommodate privacy constraints in an industrial setting. Experiments show significant improvements by our models in tackling the summarization and content validation tasks on public datasets.
