The fitness dubbed export is not clean or production-ready because the output retains an ElevenLabs watermark.

✗ Failed🧾 artifact-verifiedinput + output shownTest date not recordedElevenLabs
What was measured
Output Quality & Export

Is the final exported video clean, downloadable, and production-ready, and are there watermarks or credit restrictions?

context, not decisivetransformation

A clean export and watermark-free download matter for usability, but they do not determine whether the tool can translate, clone voice, and lip-sync well. (3 of 3 judges)

What was given, what came back

Test input: Fitness instructor short (English → Hindi) · video · group: video-translation-voice-clone-lip-sync
Input — what we sent

A short fitness/coaching video with energetic single-speaker English speech, used to test whether tools can translate into Hindi while preserving fast delivery, motivational tone, and original-face lip sync.

Why this input is hard
  • · Fast, energetic speech transcription
  • · Tone preservation for motivational fitness content
  • · English-to-Hindi translation quality
  • · Lip-sync accuracy on a moving face
  • · End-to-end dubbing workflow automation
Provenance
Observation
6a2371a9-10eb-4e08-a469-27058dfe35a9
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
first-party
Evidence state
verified
Proof shown
input + output shown
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: "elevenlabs",
  scenario: "video-translation-voice-clone-lip-sync"
})
MCP · mcp.aidemos.com/api/mcp
Free with attribution.
Same input, same check — 4 other tools
measured on Output Quality & Export
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