⭐ Triadic Audio Observer — Starter Notebook

A structural approach to understanding sound using RTT.

This notebook provides a starting scaffold for analyzing audio signals through the Triadic Audio Observer lens.

The goal is not “better EQ,” but structural clarity.

0. Setup#

import numpy as np
import matplotlib.pyplot as plt
import librosa
import librosa.display

1. Load Audio#

audio_path = "audio/sample.wav"
signal, sr = librosa.load(audio_path, sr=None)
 
print(f"Sample Rate: {sr}")

Source can be music, speech, noise, or test tones
Keep original sample rate when possible

2. Time & Frequency View#

plt.figure(figsize=(10, 3))
librosa.display.waveshow(signal, sr=sr)
plt.title("Time Domain")
plt.show()

S = np.abs(librosa.stft(signal))
librosa.display.specshow(librosa.amplitude_to_db(S, ref=np.max),
                         sr=sr, x_axis='time', y_axis='log')
plt.title("Frequency Domain")
plt.colorbar()
plt.show()

3. Regime Mapping#

regimes = {
    "R1_Physical": [
        "Air coupling",
        "Enclosure resonance",
        "Driver limitations"
    ],
    "R2_Structural": [
        "Crossover design",
        "Phase alignment",
        "Material choices"
    ],
    "R3_Perceptual": [
        "Clarity",
        "Fatigue",
        "Spatial impression"
    ]
}
regimes

4. Drift Detection#

# Example: spectral centroid over time
centroid = librosa.feature.spectral_centroid(y=signal, sr=sr)
 
plt.plot(centroid.T)
plt.title("Spectral Drift Over Time")
plt.show()

Look for instability
Look for wandering energy
Look for regime mismatch

5. Paradox Zones#

paradox_notes = [
    "High energy but low intelligibility",
    "Flat response but listener fatigue",
    "Wide bandwidth but weak presence"
]
paradox_notes

6. Coherence Mapping#

# Placeholder coherence metric
coherence_score = np.mean(centroid)
 
coherence_score

Coherence is alignment across regimes
Not loudness
Not flatness

7. Glyphic Signature (Conceptual)#

glyph_signature = {
    "Resonance": "Stable / Unstable",
    "Drift": "Low / Medium / High",
    "Coherence": "Aligned / Fragmented"
}
glyph_signature

This section is intentionally conceptual — future tools can render glyphs visually.

8. Structural Insights#

insights = [
    "Midrange coherence dominates perceived clarity",
    "Phase drift correlates with fatigue",
    "Structural alignment beats brute-force EQ"
]
insights

9. Forward Use#

Speaker design feedback
Room treatment exploration
Listening education
Comparative analysis across systems

This notebook is a starting point, not a prescription. Users are encouraged to extend, remix, and build their own observers.