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A12 Code

The layered code for the sound layer flat text leaves out.

A12 is the BantuNomics layered orthography code and codec. It starts with the ordinary spelling a model sees, then adds the sound facts that ordinary spelling does not reliably mark: vowel length, tone, downstep, phrase boundary, and voice quality.

Plain definition

A12 keeps the spelling and adds the missing layers.

The Flat Text Problem exists because ordinary text collapses a spoken Bantu form into a one-dimensional string. A12 reverses that compression in a controlled way. It treats native audio as canonical evidence, aligns that evidence to the syllable, and writes the recoverable sound facts as additive layers.

The design principle is simple: do not destroy the original orthography. Preserve the standard spelling as the base layer, then add explicit layers for the acoustic facts a machine needs but the page does not show.

A12 transform audio + spelling -> layers + confidence + provenance

What A12 is and is not

A12 is not a new alphabet. It is a codec for hidden evidence.

It preserves standard writing.

Layer 0 is the ordinary spelling. A12 does not ask communities to abandon their orthography or write everyday text differently.

It makes sound addressable.

Layers above L0 expose vowel length, tone, downstep, boundary, and voice-quality evidence so models can reason over what native speakers hear.

It is built for audit.

A12 outputs should be traceable to audio, syllable alignment, confidence, and provenance. The point is not decoration; the point is verifiable structure.

Pipeline

From waveform to usable linguistic structure.

01

Audio plus spelling

A consented native recording is paired with the ordinary spelling, for example ulebomba.

02

Syllable alignment

The word is parsed into syllables so the vowel nuclei, the tone-bearing positions, are addressable.

03

Acoustic extraction

Length, F0 contour, downstep, boundary slope, and voice-quality evidence are measured from the signal.

04

Layer assembly

A12 composes the evidence into additive orthographic layers without destroying the original spelling.

05

Enterprise output

The resulting layer bundle can support ASR, TTS, MT, pedagogy, corpus annotation, and evaluation workflows.

Codec layers

Each layer adds one missing channel.

L0

Orthography

The standard written form. It is useful for native readers, but it does not encode the full sound layer.

Plain spelling The input string as written
L1

Mora

The codec reveals concealed vowel length where the audio shows a long nucleus that ordinary spelling does not mark.

Vowel length Duration and intensity envelope
L2

Tone

Tone marks are attached to the vowel nucleus, because the syllable is the tone-bearing unit.

High and low tone marks Per-syllable F0 median, slope, and register anchor
L3

Downstep

Downstep marks places where a high tone is realized lower than expected because of tonal structure.

Lowered high-tone markers F0 contour and local register drop
L4

Phrase Boundary

The phrase edge separates statements, questions, and discourse boundaries that flat text does not expose.

L% or H% phrase edge Declination slope and final-syllable contour
L5

Voice Quality

Voice quality is a higher acoustic layer. It is not a replacement for tone; it is another channel in the signal.

Phonation / voice-quality cue H1-H2, jitter, and related acoustic features

uLebomba evidence

The collision is visible once the audio is measured.

The same flat spelling can carry different meanings because the decisive evidence lives in the signal. These artifacts show how the A12 view separates the signal, the sense axis, and the pairwise differences that flat text collapses.

uLebomba signal-to-meaning analysis
Signal-to-meaning path
uLebomba sense-axis profile
Sense-axis profile
uLebomba sense-pair matrix
Sense-pair matrix

Enterprise use

A12 turns hidden sound evidence into a product surface.

For ASR, TTS, translation, pedagogy, corpus annotation, and model evaluation, the value of A12 is that the missing sound layer becomes addressable. A model no longer sees only one token. It sees the ordinary spelling plus the layered evidence needed to separate meaning.