Beyond Controlled Comparison: Deployment Properties of Script-Aware ASR for N'Ko
This deployment paper moves beyond controlled comparison and looks at the properties that matter once script-aware ASR is expected to run on actual devices: latency, memory, failure gating, and the gap between an offline model and a live microphone.
Paper workspace
Live draft structure
Artifacts
Draft PDF
Deployment draft. Useful, but live calibration status has changed since this render.
Open artifactEditable source
Draft PDF exists. It should be updated with the current iPhone live-gate evidence before release.
Source anchors
nko-brain-scanner/paper/current/paper5_deployment.tex
nko-brain-scanner/paper/final/04-agp-deployment/paper.tex
Method tags
Ingest intersections
Status
Drafted; venue-split set prepared (four-paper release plan).
Key claims
01
A good offline result does not automatically become a usable live recognizer.
02
Deployment exposes timing, memory, and gating problems that benchmarks hide.
03
The iPhone harness should be treated as a measurement surface, not a demo claim.
Public reading note
Drafted; live calibration proof still pending.
Standard skeleton
What this paper must keep proving
problem
An offline model can look good while failing as a live user-facing recognizer.
method
Track latency, frontend parity, overfire gates, packet review, and promotion boundaries separately.
implementation
iPhone harness, CoreML encoder/head, live mic capture, calibration packet export.
data
Replayable live packets and reviewed labels, not machine output treated as truth.
evaluation
Latency, no-garbage gating, packet replay, reviewed transcript correctness, and training admissibility.
references
Mobile ASR deployment, CoreML, speech calibration, dataset governance.
openQuestions
How many reviewed packets are needed before live recognition becomes a credible product claim.
Checkpoints and references
Proof chain
Claim checkpoint
central-claim slot
Every central claim must point to a proof anchor or remain labeled as speculative.
Implementation checkpoint
implementation-map slot
Every method should identify the code path, harness, schema, or protocol that embodies it.
Evidence checkpoint
evidence-manifest slot
Every reported result should point to run IDs, packet IDs, data snapshots, commits, or review artifacts.
Reference checkpoint
references slot
Every external claim should resolve to a cited paper, benchmark, standard, or documented prior system.
Release checkpoint
release-gate slot
Every PDF needs a named condition before it can move from draft to citation-ready.