论文标题
开发生产系统，目的是在商务电话交谈中进行呼叫检测
Developing a Production System for Purpose of Call Detection in Business Phone Conversations
论文作者
论文摘要
对于接听电话的代理商，最重要的信息是给定电话的原因。如果代理商不知道客户为什么要打电话，则无法提供呼叫的支持。在本文中，我们描述了我们实施商业系统，以实时检测英语商务呼叫笔录中的呼叫声明目的。我们对与之相关的呼叫声明和语言模式的目的类型进行了详细分析，讨论一种通过引导从一组规则到神经模型来收集丰富培训数据的方法，并描述了一个由基于变压器的分类器组成的混合模型，以及通过从呼叫转录分析中利用洞察力的一组规则。在对现实生活数据进行测试时，该模型平均在各种类型的业务呼叫中达到了88.6 F1，并且推理时间较低。我们反思开发和部署系统时的挑战和设计决策。
For agents at a contact centre receiving calls, the most important piece of information is the reason for a given call. An agent cannot provide support on a call if they do not know why a customer is calling. In this paper we describe our implementation of a commercial system to detect Purpose of Call statements in English business call transcripts in real time. We present a detailed analysis of types of Purpose of Call statements and language patterns related to them, discuss an approach to collect rich training data by bootstrapping from a set of rules to a neural model, and describe a hybrid model which consists of a transformer-based classifier and a set of rules by leveraging insights from the analysis of call transcripts. The model achieved 88.6 F1 on average in various types of business calls when tested on real life data and has low inference time. We reflect on the challenges and design decisions when developing and deploying the system.
