The Relationship between Consciousness and Linguistic Data to Formalize
Keywords:
: Explainable AI, Cyberbullying, Real-Time NLP, Multi-Teacher Knowledge Distillation, XGBoost, SHAP, Emotion Detection, Sarcasm Detection, Multilingual NLP, conscious language use, symmetry principle, , positional labelling, computational linguistic encoding, syllable typology, formal notation system, rhythm-based phonology, meter and linguistic melody, ӭagyar MᲩa-siralom, Planctus ante nescia, speech processing, NLP.Abstract
This study seeks to formalize the relationship between consciousness and linguistic data through a symmetry-based approach. It proceeds from the assumption that consciousness as a biological fact and linguistic structures-especially their formally describable patterns�are mirror images of one another. The structures of conscious linguistic composition are reflected in the organization of linguistic data, while formal linguistic patterns can be traced back to the inner, rhythmic, and symmetrical architecture of consciousness. To map this relationship, the study integrates the methodological toolkits of three coequal fields: computational linguistic encoding, rhythm-based phonology, and the historical investigation of linguistic melody.
The computational linguistic encoding relies on a custom-developed system that classifies syllables within words by typology and position. At the core of the model stands a center�periphery principle: vowels constitute the center of the structure, encircled by concentrically arranged consonants. This symmetry-based approach enables precise formal annotation of the internal structure of syllables and sheds light on recurring patterns in phonological organization. The classification introduces 55 syllable types grounded in five basic structures (e.g., open, closed, reduced, etc.), augmented by positional labelling that records whether a syllable is word-initial, word-medial, or word-final.
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