How the Brain Processes Speech as a Blueprint for Universal Translation

This article proposes that the most promising route towards universal translation lies in modelling how the human brain processes speech rather than relying solely on word-to-word or sentence-to-sentence conversion. Drawing on findings from cognitive neuroscience, semantic mapping, neural language reconstruction, and multilingual machine translation, the paper argues that speech comprehension unfolds through layered transformations from acoustic input to increasingly abstract representations of meaning. On this basis, the article advances a theoretical framework in which languages are treated as different expressive surfaces over deeper intermediate neural-semantic representations. The central innovation of the paper is its claim that the brain’s hierarchical transformation of speech into meaning can serve as the conceptual blueprint for universal translation. Rather than treating neuroscience as a loose metaphor, the article positions shared cognitive architecture as the foundation for translation design. In this framework, translation is redefined as the inference of intermediate representational states and their controlled regeneration in another language. The contribution is both theoretical and technical. Theoretically, it reframes language as a process of neural representation rather than a static symbolic code, and it situates universality first in human cognition and only secondarily in computational systems. Technically, it supports the development of translation systems with explicit intermediate semantic layers, hierarchical architectures, and evaluation methods informed by how the brain organises speech and meaning. The article, therefore, offers a new interdisciplinary foundation for thinking about universal translation.