Cognitively-inspired representational approach to meaning in machine dialogue

作者：

Highlights：

• We propose a computational model for meaning representation in machine dialogue.

• It is aimed at robust processing of the user’s utterances without a preset grammar.

• It is inspired by neuroimaging studies on working memory and Broca’s aphasia.

• We show that it can be generalized over different interaction domains.

• We report on a framework for end-user programming of adaptive dialogue systems.

摘要

•We propose a computational model for meaning representation in machine dialogue.•It is aimed at robust processing of the user’s utterances without a preset grammar.•It is inspired by neuroimaging studies on working memory and Broca’s aphasia.•We show that it can be generalized over different interaction domains.•We report on a framework for end-user programming of adaptive dialogue systems.

论文关键词：Human–machine dialogue,Meaning representation,Cognition,Attention,Focus tree,Broca’s aphasia

论文评审过程：Received 17 November 2013, Revised 1 May 2014, Accepted 4 May 2014, Available online 10 May 2014.

论文官网地址：https://doi.org/10.1016/j.knosys.2014.05.001