衡量和实施词法调整:系统文献综述

IF 3.1 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Sumit Srivastava , Suzanna D. Wentzel , Alejandro Catala , Mariët Theune
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引用次数: 0

摘要

词汇对齐是人与人对话中经常出现的一种现象,即对话者在对话过程中趋于使用相同的术语和短语来表达相同的基本概念。对齐(语言)是人类为使对话者在不同语言知识和特征层面上更好地交流而使用的一种机制,词汇对齐就是其中之一。现有文献表明,对齐在人与人之间的交流中具有重要作用,在人机交流中也是有益的。过去,人们提出了各种方法来测量人与人对话中的词汇对齐情况,并将其应用到对话代理中。在本研究中,我们分析了现有的词性一致度测量方法,并剖析了在会话代理中实现词性一致度的方法,以实现人机交互的个性化。我们提出了一套此类方法应满足的新标准,并讨论了对现有方法可能做出的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Measuring and implementing lexical alignment: A systematic literature review
Lexical Alignment is a phenomenon often found in human–human conversations, where the interlocutors converge during a conversation to use the same terms and phrases for the same underlying concepts. Alignment (linguistic) is a mechanism used by humans for better communication between interlocutors at various levels of linguistic knowledge and features, and one of them is lexical. The existing literature suggests that alignment has a significant role in communication between humans, and is also beneficial in human–agent communication. Various methods have been proposed in the past to measure lexical alignment in human–human conversations, and also to implement them in conversational agents. In this research, we carry out an analysis of the existing methods to measure lexical alignment and also dissect methods to implement it in a conversational agent for personalizing human–agent interactions. We propose a new set of criteria that such methods should meet and discuss the possible improvements that can be made to existing methods.
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来源期刊
Computer Speech and Language
Computer Speech and Language 工程技术-计算机:人工智能
CiteScore
11.30
自引率
4.70%
发文量
80
审稿时长
22.9 weeks
期刊介绍: Computer Speech & Language publishes reports of original research related to the recognition, understanding, production, coding and mining of speech and language. The speech and language sciences have a long history, but it is only relatively recently that large-scale implementation of and experimentation with complex models of speech and language processing has become feasible. Such research is often carried out somewhat separately by practitioners of artificial intelligence, computer science, electronic engineering, information retrieval, linguistics, phonetics, or psychology.
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