A chatbot response generation system

Jasper Feine, Stefan Morana, A. Maedche
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引用次数: 4

Abstract

Developing successful chatbots is a non-trivial endeavor. In particular, the creation of high-quality natural language responses for chatbots remains a challenging and time-consuming task that often depends on high-quality training data and deep domain knowledge. As a consequence, it is essential to engage experts in the chatbot response development process which have the required domain knowledge. However, current tool support to engage domain experts in the response generation process is limited and often does not go beyond the exchange of decoupled prototypes and spreadsheets. In this paper, we present a system that enables chatbot developers to efficiently engage domain experts in the chatbot response generation process. More specifically, we introduce the underlying architecture of a system that connects to existing chatbots via an API, provides two improvement mechanisms for domain experts to improve chatbot responses during their chatbot interaction, and helps chatbot developers to review the collected response improvements with a sentiment supported review dashboard. Overall, the design of the system and its improvement mechanisms are useful extensions for chatbot development systems in order to support chatbot developers and domain experts to collaboratively enhance the natural language responses of a chatbot.
一个聊天机器人响应生成系统
开发成功的聊天机器人并非易事。特别是,为聊天机器人创建高质量的自然语言响应仍然是一项具有挑战性和耗时的任务,通常依赖于高质量的训练数据和深入的领域知识。因此,在聊天机器人响应开发过程中聘请具有所需领域知识的专家至关重要。然而,在响应生成过程中使用领域专家的当前工具支持是有限的,并且通常不会超出解耦原型和电子表格的交换。在本文中,我们提出了一个系统,使聊天机器人开发人员能够有效地在聊天机器人响应生成过程中聘请领域专家。更具体地说,我们介绍了一个系统的底层架构,该系统通过API连接到现有的聊天机器人,为领域专家提供了两种改进机制,以便在聊天机器人交互过程中改进聊天机器人的响应,并帮助聊天机器人开发人员使用情感支持的审查仪表板审查收集到的响应改进。总体而言,该系统的设计及其改进机制是对聊天机器人开发系统的有益扩展,以支持聊天机器人开发人员和领域专家协同增强聊天机器人的自然语言响应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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