会话式机器阅读理解综述

doi:10.3778/j.issn.1673-9418.2102039

摘要/Abstract

摘要：

机器阅读理解（MRC）是一个受数据集推动的研究领域，其目标是让机器在理解文章内容的基础上能够正确回答相关问题。早期受数据集限制，机器阅读理解任务大多局限于单轮问答，问答对之间缺少依赖关系。而会话问答（ConvQA）是使机器在帮助人类获取信息时可以进行连续主题的人机交互过程。近年来，随着机器阅读理解数据集和深度神经网络的发展，研究人员将机器阅读理解与会话问答结合，形成更为复杂真实的会话式机器阅读理解（CMC），这极大地推动了机器阅读理解领域的发展。对近几年会话式机器阅读理解相关最新研究进展从三方面归纳总结：首先阐述该任务的定义、所面临的挑战以及相关数据集的特性；然后归纳总结当前最新模型的架构及其研究进展，着重介绍会话历史嵌入表示以及会话推理所使用的相关技术方法；最后梳理分析当前会话式机器阅读理解模型，并对未来研究重点和研究方法进行展望。

关键词: 多轮对话, 机器阅读理解（MRC）, 会话问答（ConvQA）

Abstract:

Machine reading comprehension (MRC) is a research field driven by datasets. The task of MRC is to make the machine correctly answer relevant questions on the basis of understanding the natural language text. But limited by datasets, most of the machine reading comprehension tasks are single-turn question answering, and there is no dependency between question answering pairs. Conversational question answering (ConvQA) is the human-computer process that enables the machine to carry out continuous topics when it helps human to obtain information. In recent years, with the development of MRC datasets and deep neural networks, researchers combine machine reading com-prehension and conversational question answering to form a new more complex field, conversational machine com-prehension (CMC). This has greatly boosted the field of MRC. This paper summarizes the latest research progress of CMC in recent years from three aspects. Firstly, it describes the definition of CMC task, the challenges and the characteristics of the datasets. Then, it summarizes the research progress and the current architecture of the latest models, and focuses on the relevant technical methods used in conversational history embedding and conversational reasoning. Finally, this paper analyzes the current model of CMC, and prospects the future research hotspots and methods of CMC.

Key words: multi-turn conversation, machine reading comprehension (MRC), conversational question answering (ConvQA)

李堃, 李艳玲, 林民. 会话式机器阅读理解综述[J]. 计算机科学与探索, 2021, 15(9): 1607-1618.

LI Kun, LI Yanling, LIN Min. Review of Conversational Machine Reading Comprehension[J]. Journal of Frontiers of Computer Science and Technology, 2021, 15(9): 1607-1618.

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