文本情感对话系统研究综述

doi:10.3778/j.issn.1673-9418.2012012

摘要/Abstract

摘要：

对话系统作为人机交互的重要方式，有着广泛的应用前景。现有的对话系统专注于解决语义一致性和内容丰富性等问题，对于提高人机交互以及产生人机共鸣方向的研究关注度不高。如何让生成的语句在具有语义相关性的基础上更自然地与用户交流是当前对话系统面临的主要问题之一。首先对对话系统进行了整体情况的概括。接着介绍了情感对话系统中的对话情绪感知和情感对话生成两大任务，并分别调研归纳了相关方法。对话情绪感知任务大致分为基于上下文和基于用户信息两类方法。情感对话生成的方法包括规则匹配算法、指定情感回复的生成模型和不指定情感回复的生成模型，并从情绪数据类别和模型方法等方面进行了对比分析。然后总结整理了两大任务下数据集的特点和链接便于后续的研究，并归纳了当前情感对话系统中不同的评估方法。最后对情感对话系统的工作进行了总结和展望。

关键词: 情感对话系统, 对话情绪感知, 情感对话生成

Abstract:

As an important way of human-computer interaction, the dialogue system has broad application prospects. Existing dialogue systems focus on solving problems such as semantic consistency and content richness and paying little attention to improving human-computer interaction and human-computer resonance. How to make the generated sentences communicate with users more naturally on the basis of semantic relevance is one of the main problems in current dialogue system. First, it summarizes the overall situation of the dialogue system. Then it introduces the two major tasks of dialogue emotion perception and emotional dialogue generation in the emotional dialogue system. And further it investigates and summarizes related methods respectively. Dialogue emotion perception tasks are roughly divided into context-based and user-based methods. The emotional dialogue generation methods include rule matching algorithms, specified emotional response generation models, and non-specified emotional response generation models. The models are compared and analyzed in terms of emotional data categories and model methods. Next, for subsequent research, it summarizes characteristics and links of the data sets under the two major tasks. Further, different evaluation methods in the current emotional dialogue system are summarized. Finally, the work of the emotional dialogue system is summarized and prospected.

Key words: emotional dialogue system, dialogue emotional perception, generation of emotional dialogue

庄寅, 刘箴, 刘婷婷, 王媛怡, 刘翠娟, 柴艳杰. 文本情感对话系统研究综述[J]. 计算机科学与探索, 2021, 15(5): 825-837.

ZHUANG Yin, LIU Zhen, LIU Tingting, WANG Yuanyi, LIU Cuijuan, CHAI Yanjie. Survey of Affective-Based Dialogue System[J]. Journal of Frontiers of Computer Science and Technology, 2021, 15(5): 825-837.

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