当前位置: X-MOL 学术arXiv.cs.LO › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Talking Space: inference from spatial linguistic meanings
arXiv - CS - Logic in Computer Science Pub Date : 2021-09-14 , DOI: arxiv-2109.06554
Vincent Wang-Mascianica, Bob Coecke

This paper concerns the intersection of natural language and the physical space around us in which we live, that we observe and/or imagine things within. Many important features of language have spatial connotations, for example, many prepositions (like in, next to, after, on, etc.) are fundamentally spatial. Space is also a key factor of the meanings of many words/phrases/sentences/text, and space is a, if not the key, context for referencing (e.g. pointing) and embodiment. We propose a mechanism for how space and linguistic structure can be made to interact in a matching compositional fashion. Examples include Cartesian space, subway stations, chesspieces on a chess-board, and Penrose's staircase. The starting point for our construction is the DisCoCat model of compositional natural language meaning, which we relax to accommodate physical space. We address the issue of having multiple agents/objects in a space, including the case that each agent has different capabilities with respect to that space, e.g., the specific moves each chesspiece can make, or the different velocities one may be able to reach. Once our model is in place, we show how inferences drawing from the structure of physical space can be made. We also how how linguistic model of space can interact with other such models related to our senses and/or embodiment, such as the conceptual spaces of colour, taste and smell, resulting in a rich compositional model of meaning that is close to human experience and embodiment in the world.

中文翻译:

谈话空间:从空间语言意义推断

这篇论文涉及自然语言与我们周围生活的物理空间的交集,我们观察和/或想象其中的事物。语言的许多重要特征都具有空间内涵,例如,许多介词(如 in、next to、after、on 等)基本上都是空间的。空格也是许多单词/短语/句子/文本的含义的关键因素,如果不是关键,则空格是参考(例如指向)和体现的上下文。我们提出了一种机制,可以使空间和语言结构以匹配的组合方式进行交互。例子包括笛卡尔空间、地铁站、棋盘上的棋子和彭罗斯的楼梯。我们构建的起点是组合自然语言含义的 DisCoCat 模型,我们放松以适应物理空间。我们解决了在一个空间中有多个代理/对象的问题,包括每个代理对该空间具有不同能力的情况,例如,每个棋子可以做出的特定移动,或者一个人可能能够达到的不同速度。一旦我们的模型就位,我们将展示如何从物理空间结构中进行推断。我们还研究了空间的语言模型如何与其他与我们的感官和/或具身相关的模型相互作用,例如颜色、味觉和嗅觉的概念空间,从而产生接近人类经验和世界上的体现。包括每个代理相对于该空间具有不同能力的情况,例如,每个棋子可以进行的特定移动,或者一个人可能能够达到的不同速度。一旦我们的模型就位,我们将展示如何从物理空间结构中进行推断。我们还研究了空间的语言模型如何与其他与我们的感官和/或具身相关的模型相互作用,例如颜色、味觉和嗅觉的概念空间,从而产生接近人类经验和世界上的体现。包括每个代理相对于该空间具有不同能力的情况,例如,每个棋子可以进行的特定移动,或者一个人可能能够达到的不同速度。一旦我们的模型就位,我们将展示如何从物理空间结构中进行推断。我们还研究了空间的语言模型如何与其他与我们的感官和/或具身相关的模型相互作用,例如颜色、味觉和嗅觉的概念空间,从而产生接近人类经验和世界上的体现。
更新日期:2021-09-15
down
wechat
bug