Tucker Say'z — Analysis Methodology

This page documents how Tucker Say'z interprets dog vocalizations. It's AI-interpreted analysis — a fun way to understand your dog better, grounded in real acoustic features and a database of canine behavior research.

What we measure

For every bark or vocalization you upload, Tucker Say'z extracts five acoustic features:

• Pitch contour — the rise and fall of the fundamental frequency
• Duration — length of the vocalization
• Syllable structure — number and timing of distinct syllables
• Harmonic quality — the tonal/harmonic character of the sound
• Energy — overall intensity and amplitude

These are the same broad feature classes used in published canine vocalization research — not gimmick pattern-matching.

How interpretation works

The acoustic features are interpreted by an AI model trained on a database of dog behavior studies. The output is a human-readable interpretation (for example, "a polite request" at 80% confidence) — always labeled as AI-interpreted, never presented as a definitive claim of what your dog is feeling.

The self-correcting loop

When you confirm or correct an analysis, that feedback is stored and exported as training data for the next model update. The more dog owners participate, the more accurate the interpretation becomes — for your dog and for every dog in the community. This is a real mechanism: corrections feed the retraining pipeline.

Privacy

Audio is analyzed for its acoustic features, then discarded. We never store your recording. Only the features are kept, and you control your data.

Tucker Say'z is a fun, AI-powered tool for understanding your dog better. It is not a veterinary diagnostic. Consult a veterinarian for behavioral or medical concerns.

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