The cleaned audio kept the speaker's original natural tone, clarity, and speaking style, with no significant robotic effects, pitch changes, or speech distortion.

✓ Worked🧾 artifact-verifiedinput + output shownTest date not recordedElevenLabs Voice Isolator
What was measured
Voice preservation

After cleanup, does the voice still sound natural, or hollow, robotic, underwater, or artifacted?

decisive for this rankingtransformation

Noise cleanup is only useful if the speech still sounds natural and intelligible after processing. (3 of 3 judges)

What was given, what came back

Test input: Indoor AC + Fan Background Noise · audio · group: background-noise-removal
Input — what we sent
0:00 / 0:00
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Indoor AC + Fan Background Noise

A real-world indoor speech recording with continuous background noise from both an air conditioner and a fan. It is designed to test whether tools can suppress overlapping mechanical noise while preserving speech naturalness.

Why this input is hard
  • · Removal of multiple overlapping indoor mechanical noises
  • · Speech enhancement and isolation
  • · Voice quality preservation under steady noise
  • · Minimal-artifact background noise suppression
Output — unretouched
0:00 / 0:00
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Provenance
Observation
a9c78f8e-69a5-44b2-aa31-e4b571ce95a0
Evidence run
189e3005-33f2-4481-924e-334542fcda87
Study
Remove Background Noise from Audio and Video Recordings Using AI
Research task
86ba6cyhe
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-voice-isolator",
  scenario: "background-noise-removal"
})
MCP · mcp.aidemos.com/api/mcp
Free with attribution.
Same input, same check — 5 other tools
measured on Voice preservation
Real inputs and real outputs, no retouching · every cell queryable via API & MCP · aidemos.com