Testing challenges for NLP-intensive bots

Jordi Cabot, L. Burgueño, R. Clarisó, Gwendal Daniel, Jorge Perianez-Pascual, Roberto Rodríguez-Echeverría
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引用次数: 4

Abstract

The popularity of bots is on the rise, with many bots able to interact with users via a chat or voice interface thanks to the embedding of a Natural Language Processing (NLP) component. Still, companies often express concerns about the quality of such bots, as their malfunctioning could have a severe impact on the company revenue or image. Unfortunately, the field of testing NLP-intensive bots is still in its infancy. This paper aims to characterize the testing properties and techniques (and their adaptation) relevant to this type of bots. We believe this will be helpful as a reference framework to compare and evaluate future bot testing research initiatives.
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对nlp密集型机器人的测试挑战
机器人的受欢迎程度正在上升,由于嵌入了自然语言处理(NLP)组件,许多机器人能够通过聊天或语音界面与用户交互。不过,企业经常对这类机器人的质量表示担忧,因为它们的故障可能会对公司的收入或形象产生严重影响。不幸的是,测试nlp密集型机器人的领域仍处于起步阶段。本文旨在描述与此类机器人相关的测试属性和技术(及其适应性)。我们相信这将有助于作为一个参考框架来比较和评估未来的机器人测试研究计划。
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