Lip sync is good on some inputs, described as more precise in one case and good for slow to medium speech, but it becomes weaker on fast speech with slight delay, sync inconsistencies, and slightly off audio-video alignment.
What was measured
Lip Sync Accuracy
Does the dubbed audio visually match lip movements in the original video?
decisive for this rankingtransformation
The ranking is specifically about lip sync, so visual alignment of speech to mouth movement is a core success criterion. (3 of 3 judges)
What was given, what came back
Input — what we sent
No input — this is a capability finding
The observation is about the tool itself rather than one test input, so there is nothing to show on this side by design.
Output — unretouched
No output artifact
The verdict rests on the tester's written observation alone — no file was captured for this cell.
Provenance
- Observation
- b5a31752-2da6-425a-869b-54e1e2ab4038
- Evidence run
- ec1dd100-6af8-4f49-8f19-b78492702b14
- Study
- Translate Videos with Voice Cloning and Lip Sync Using AI
- Research task
- 86b96dfpf
- Tested at
- not recorded
- Source
- aggregate-synthesis
- Evidence state
- observed
- Proof shown
- no artifact
- 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: "dubverse"
})MCP · mcp.aidemos.com/api/mcp
Free with attribution.
Same input, same check — 0 other tools
measured on Lip Sync Accuracy
No other tool was measured on this criterion for this input.
This evidence is published in
From the same study (page rebuilt from a later run)
Real inputs and real outputs, no retouching · every cell queryable via API & MCP · aidemos.com