论文标题
语言（重新）建模：迈向体现语言理解
Language (Re)modelling: Towards Embodied Language Understanding
论文作者
论文摘要
尽管自然语言理解（NLU）正在迅速发展，但今天的技术与类似人类的语言理解不同，尤其是其较低的效率，可解释性和概括性。这项工作提出了一种基于具体认知语言学（ECL）的宗旨的表示和学习的方法。根据ECL的说法，自然语言本质上是可执行的（例如编程语言），这是由心理模拟和隐喻映射驱动的，对结构的层次结构组成，而通过体现的互动学到了学会。该立场论文认为，通过隐喻推理和模拟对接地的使用将极大地使NLU系统受益，并提出了系统架构以及实现这一愿景的路线图。
While natural language understanding (NLU) is advancing rapidly, today's technology differs from human-like language understanding in fundamental ways, notably in its inferior efficiency, interpretability, and generalization. This work proposes an approach to representation and learning based on the tenets of embodied cognitive linguistics (ECL). According to ECL, natural language is inherently executable (like programming languages), driven by mental simulation and metaphoric mappings over hierarchical compositions of structures and schemata learned through embodied interaction. This position paper argues that the use of grounding by metaphoric inference and simulation will greatly benefit NLU systems, and proposes a system architecture along with a roadmap towards realizing this vision.
