论文标题
自动移动和其他移动：日语的量子分类基础
Self-move and Other-move: Quantum Categorical Foundations of Japanese
论文作者
论文摘要
这项工作的目的是为创建量子自然语言处理（QNLP）翻译程序的更大目标做出贡献。这项工作基于基于类别理论在英语上完成的先前工作来贡献日语的原始图形表示。强调英语和日语之间的依恋差异，以帮助解决当前研究体系中的英语偏见。此外，提出了这些图表的拓扑原理和许多进一步研究的潜在途径。为什么这项工作很重要？在数千年中，数百种语言与跨时间和地理位置的人类互动的演变相吻合。这些语言是人类生存，经验，繁荣和过上美好生活的基础。但是，它们也是人群之间最强的障碍。在过去的几十年中，自然语言处理的进步（NLP）使得不具有共同语言或文化的个人之间的差距变得更加容易。诸如Google Translate和Deepl之类的工具比以往任何时候都更容易与全球人分享我们的经验。然而，这些工具仍然不足，因为它们无法流利地传达我们的思想，使人们感到焦虑和尴尬。尤其如此，这是由英语和日语等基本不同文化所生的语言。量子计算机提供了实现翻译流利度的最佳机会，因为它们更适合模拟自然世界和自然现象，例如自然语音。 关键词：类别理论，迪斯科舞，野外，日本语法，英语语法，翻译，拓扑，量子自然语言处理，自然语言处理
The purpose of this work is to contribute toward the larger goal of creating a Quantum Natural Language Processing (QNLP) translator program. This work contributes original diagrammatic representations of the Japanese language based on prior work that accomplished on the English language based on category theory. The germane differences between the English and Japanese languages are emphasized to help address English language bias in the current body of research. Additionally, topological principles of these diagrams and many potential avenues for further research are proposed. Why is this endeavor important? Hundreds of languages have developed over the course of millennia coinciding with the evolution of human interaction across time and geographic location. These languages are foundational to human survival, experience, flourishing, and living the good life. They are also, however, the strongest barrier between people groups. Over the last several decades, advancements in Natural Language Processing (NLP) have made it easier to bridge the gap between individuals who do not share a common language or culture. Tools like Google Translate and DeepL make it easier than ever before to share our experiences with people globally. Nevertheless, these tools are still inadequate as they fail to convey our ideas across the language barrier fluently, leaving people feeling anxious and embarrassed. This is particularly true of languages born out of substantially different cultures, such as English and Japanese. Quantum computers offer the best chance to achieve translation fluency in that they are better suited to simulating the natural world and natural phenomenon such as natural speech. Keywords: category theory, DisCoCat, DisCoCirc, Japanese grammar, English grammar, translation, topology, Quantum Natural Language Processing, Natural Language Processing
