Beyond Babel: A Case Study in Vectorial-Semantic Music Translation and Generation

This paper presents an experimental case study on the use of advanced generative
Artificial Intelligence (AI) for the cross-cultural translation of music. Moving beyond traditional linguistic translation, this work explores the concept of "semantic translation," wherein AI models operate within a high-dimensional vector space of meaning, independent of any specific human language. We hypothesize that this "semantic metaspace" allows for the translation of not just words, but the core artistic intent, cultural context, and emotional resonance of a creative work. To test this, a complex, slang-rich song by the Russian band Leningrad was re-interpreted and then translated into German and three distinct semantic "depths" of English using a sophisticated AI system and the Suno music generation platform. The results demonstrate that AI can successfully navigate complex cultural and linguistic nuances, including idiomatic slang, to produce artistically coherent and emotionally resonant works in target languages. This process, termed the creation of a "meta-song," suggests we are on the cusp of a creative explosion, where art can be dynamically re-localized, fostering a more integrated and fluid global cultural landscape.