This white paper presents a cross-domain framework for evaluating speech in terms of its systemic coherence and communicative impact. Drawing from principles in information theory [1], systems science [6], and metaphorical extensions of quantum entanglement [2], we propose a model that assesses the harmonic value of any verbal expression. The model is built upon the formula H = QE / (1 + S), where H denotes the harmonic quality, QE reflects relational coherence, and S quantifies semantic entropy or contextual noise.
Initially conceived as a tool for analyzing political rhetoric, this framework reveals broader utility in corporate communication, education, AI output filtering, coaching, and leadership analysis. As speech increasingly shapes cultural and institutional outcomes, the need to measure its constructive or destructive tendencies becomes urgent.
Speech that enhances connection, builds trust, and clarifies intent can be distinguished from speech that fragments, obscures, or polarizes. Our model captures this distinction in a single value, harmonizing interpretability and scalability.
Incorporating this metric into existing communication channels and feedback systems could help organizations detect early signs of toxicity or incoherence. Leaders can receive real-time feedback, educators can improve clarity, and AI can be tuned for more ethical interaction.
This white paper introduces the model, explains its theoretical foundations, illustrates application scenarios, and proposes a modular implementation architecture. The ultimate aim is to shift how we interpret and engineer language — from merely persuasive to harmonically generative.