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The Design and Implementation of XiaoIce, an Empathetic Social Chatbot

Published: 01 March 2020 Publication History

Abstract

This article describes the development of Microsoft XiaoIce, the most popular social chatbot in the world. XiaoIce is uniquely designed as an artifical intelligence companion with an emotional connection to satisfy the human need for communication, affection, and social belonging. We take into account both intelligent quotient and emotional quotient in system design, cast human–machine social chat as decision-making over Markov Decision Processes, 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 intent, and responds to user needs throughout long conversations. Since the release in 2014, XiaoIce has communicated with over 660 million active 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.

Cited By

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  • (2024)Behaviors and Perceptions of Human-Chatbot Interactions Based on Top Active Users of a Commercial Social ChatbotProceedings of the ACM on Human-Computer Interaction10.1145/36870228:CSCW2(1-28)Online publication date: 8-Nov-2024
  • (2024)Personality-affected Emotion Generation in Dialog SystemsACM Transactions on Information Systems10.1145/365561642:5(1-27)Online publication date: 13-May-2024
  • (2024)Kavy: Fostering Language Speaking Skills and Self-Confidence Through Conversational AIProceedings of the Augmented Humans International Conference 202410.1145/3652920.3652944(226-236)Online publication date: 4-Apr-2024
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        Published In

        cover image Computational Linguistics
        Computational Linguistics  Volume 46, Issue 1
        March 2020
        247 pages
        ISSN:0891-2017
        EISSN:1530-9312
        Issue’s Table of Contents
        This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits you to copy and redistribute in any medium or format, for non-commercial use only, provided that the original work is not remixed, transformed, or built upon, and that appropriate credit to the original source is given. For a full description of the license, please visit https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode.

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        MIT Press

        Cambridge, MA, United States

        Publication History

        Published: 01 March 2020
        Published in COLI Volume 46, Issue 1

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        Cited By

        View all
        • (2024)Behaviors and Perceptions of Human-Chatbot Interactions Based on Top Active Users of a Commercial Social ChatbotProceedings of the ACM on Human-Computer Interaction10.1145/36870228:CSCW2(1-28)Online publication date: 8-Nov-2024
        • (2024)Personality-affected Emotion Generation in Dialog SystemsACM Transactions on Information Systems10.1145/365561642:5(1-27)Online publication date: 13-May-2024
        • (2024)Kavy: Fostering Language Speaking Skills and Self-Confidence Through Conversational AIProceedings of the Augmented Humans International Conference 202410.1145/3652920.3652944(226-236)Online publication date: 4-Apr-2024
        • (2024)Beyond Text and Speech in Conversational Agents: Mapping the Design Space of AvatarsProceedings of the 2024 ACM Designing Interactive Systems Conference10.1145/3643834.3661563(1875-1894)Online publication date: 1-Jul-2024
        • (2024)Building Better AI Agents: A Provocation on the Utilisation of Persona in LLM-based Conversational AgentsProceedings of the 6th ACM Conference on Conversational User Interfaces10.1145/3640794.3665887(1-6)Online publication date: 8-Jul-2024
        • (2024)Marrying Dialogue Systems with Data Visualization: Interactive Data Visualization Generation from Natural Language ConversationsProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3637528.3671935(2733-2744)Online publication date: 25-Aug-2024
        • (2024)Leveraging Large Language Models to Power Chatbots for Collecting User Self-Reported DataProceedings of the ACM on Human-Computer Interaction10.1145/36373648:CSCW1(1-35)Online publication date: 26-Apr-2024
        • (2024)Conversational Bibliographic SearchProceedings of the 2024 Conference on Human Information Interaction and Retrieval10.1145/3627508.3638337(445-448)Online publication date: 10-Mar-2024
        • (2024)Understanding Public Perceptions of AI Conversational Agents: A Cross-Cultural AnalysisProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642840(1-17)Online publication date: 11-May-2024
        • (2024)CloChat: Understanding How People Customize, Interact, and Experience Personas in Large Language ModelsProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642472(1-24)Online publication date: 11-May-2024
        • Show More Cited By

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