The word-level highlight system stayed locked to the active words during fast speech, with no visible drift across the timeline.

✓ Worked🧾 artifact-verifiedinput onlyTest date not recordedAutoCaption.io
What was measured
Timing precision

How accurately the tool syncs captions at the word level so highlights land on the right word at the right moment.

transformation

What was given, what came back

Test input: AI demos chatbot short · video
Input — what we sent
Input file 1 — as supplied
Input file 2 — as supplied
AI demos chatbot short

Fast-speaking single-speaker clip used to stress whether visual word-by-word highlighting stays synchronized with rapid audio.

Why this input is hard
  • · high-speed audio-visual sync
  • · caption timing under rapid speech
  • · sync drift detection
  • · highlight lag during fast delivery
Output — unretouched
No output artifact
The verdict rests on the tester's written observation alone — no file was captured for this cell.
Provenance
Observation
a2b85065-c712-48d4-abc4-99a89fb50d22
Evidence run
476abcc6-bd47-4f8c-8d81-d7ff6f5293a2
Study
Generate Animated Captions with Effects for Videos
Research task
86ba42c3z
Tested at
not recorded
Source
first-party
Evidence state
verified
Proof shown
input only
Cost / latency
not captured
Repeat run
not captured
Tester
not captured

The last three rows are honest blanks, not placeholders — our capture has no field for them yet.

Query this
get_evidence({
  tool: "autocaption-io"
})
MCP · mcp.aidemos.com/api/mcp
Free with attribution.
Same input, same check — 3 other tools
measured on Timing precision
Real inputs and real outputs, no retouching · every cell queryable via API & MCP · aidemos.com