This paper describes the development of the Microsoft XiaoIce system, the most popular social chatbot in the world. XiaoIce is uniquely designed as an AI companion with an emotional connection to satisfy the human need for communication, affection, and social belonging. We take into account both intelligent quotient (IQ) and emotional quotient (EQ) in system design, cast human-machine social chat as decision-making over Markov Decision Processes (MDPs), and optimize XiaoIce for long-term user engagement, measured in expected Conversation-turns Per Session (CPS). We detail the system architecture and key components including dialogue manager, core chat, skills, and an empathetic computing module. We show how XiaoIce dynamically recognizes human feelings and states, understands user intents, and responds to user needs throughout long conversations. Since the release in 2014, XiaoIce has communicated with over 660 million users and succeeded in establishing long-term relationships with many of them. Analysis of large-scale online logs shows that XiaoIce has achieved an average CPS of 23, which is significantly higher than that of other chatbots and even human conversations.
翻译:本文描述了微软小冰系统(微软小冰系统,世界上最受欢迎的社交聊天室)的发展。小冰是一个独特的AI伴侣,具有情感联系,以满足人类对沟通、情感和社会归属的需要。我们在系统设计中既考虑到智能商数(IQ),又考虑到情感商数(EQ),在系统设计中既考虑到智能商数(IQ)和情感商数(EQ),将人机社会聊天作为Markov决策程序(MDPs)的决策手段,又根据预期的谈话周期每次会议(CPS)衡量,优化小冰的长期用户参与。我们详细介绍了系统结构和关键组成部分,包括对话管理者、核心聊天、技能和同情性计算模块。我们展示了小冰如何动态地认识人类的感情和状态,理解用户的意图,并在整个长期对话中响应用户的需要。自2014年发布以来,小冰与超过6.6亿用户进行了沟通,并成功地与其中许多人建立了长期关系。对大型在线日的分析显示,小冰平均达到23个CPS,大大高于其他聊天室甚至人对话。