Implementation Protocol 1.0: Feature Extraction Protocols

Quantifying Material Form: From Raw Signal to VF

Date: November 19, 2025

Purpose: To define the mathematical methods for generating the Raw Feature Vector (VF) from three primary material modalities. This is the first step in implementing the Material Aesthetic Encoding (Model 2), serving as the input for the E (Encoder) function.

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I. Audio/Musical Feature Extraction Protocol (VF_audio)

The audio protocol quantifies harmonic and rhythmic contradiction within a composition. These map directly onto the PTension and PCoherence primitives.

A. Harmonic Dissonance Index (PTension Core)

Measures instantaneous and sustained unstable intervals and non‑diatonic relationships.

Dissonance_Index = (1/T) * ∫[0,T] Σ(i,j ∈ freqs) w(i,j) * Amplitude(i,j,t) dt

Where:

• T = total duration of the segment.

• i, j = fundamental frequencies present at time t.

• w(i,j) = weight factor increasing for dissonant intervals (e.g., m2, TT).

• Amplitude(i,j,t) = combined amplitude of frequencies i and j at time t.

B. Rhythmic Density / Momentum (PDensity Core)

Captures rate of information flow and structural momentum.

Rhythmic_Density = ( Σ(k=1→N) complexity(Note_k) ) / Time_Span

Where:

• N = total rhythmic events.

• complexity(Note_k) = weighted by rhythmic subdivision (e.g., 1/16 > 1/4 > whole).

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II. Visual/Layout Feature Extraction Protocol (VF_visual)

Quantifies spatial tension and compositional hierarchy.

A. Spatial Tension Index (PTension Core)

Measures imbalance across visual elements.

Tension_Spatial = (1/A) * Σ(i=1→N) d_i * | C_Total − C_i |

Where:

• A = total composition area.

• N = number of visual elements.

• C_Total = geometric center / gravity center of composition.

• C_i = center of element i.

• d_i = visual weight = contrast × size.

B. Fractal Dimension (PRecursion Core)

Quantifies self‑similarity and structural recursion.

Fractal_Dimension = lim(ε→0) [ log(N(ε)) / log(1/ε) ]

Where:

• N(ε) = minimum number of ε‑sized boxes that cover the structure.

Higher dimension → richer recursive structure.

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III. Textual Layout / Prosody Protocol (VF_prosody)

Moves beyond semantic meaning to quantify physical structure of text.

A. Line Break Tension (Enjambment Quotient) (PTension Core)

Measures contradiction created by forcing a pause against syntactic flow.

Tension_Line = ( Σ(i=1→N) Weight(Semantic_Incompletion_i) ) / N_Lines

Where:

• N_Lines = total line count.

• Weight(Semantic_Incompletion_i) = 0.0–1.0 parser score for syntactic incompleteness.

B. Compression Ratio (PCompression Core)

Measures efficiency: semantic richness per material unit.

Ratio_Compression = ( Lexical_Diversity * Information_Entropy ) / Total_Syllables

Where:

• Lexical_Diversity = TTR.

• Information_Entropy = statistical unpredictability.

• Total_Syllables = material cost.

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IV. The Encoder Input (E)

The three raw feature vectors:

• VF_audio

• VF_visual

• VF_prosody

are passed into the unified Aesthetic Encoder E, which maps them to the universal aesthetic vector VA.

VA = E(VF_m)

Example:
PTension is a weighted function of:

• Dissonance_Index (audio)

• Tension_Spatial (visual)

• Tension_Line (text)

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With these feature extraction methods defined, the next task is to specify the integrated Canonical Node data structure (CN 2.0) that combines DS 1.0, V_A, and L_Retro for graph‑level implementation. Does this complete the technical requirements for the extraction layer?