The tool handled continuous AC hum and breathing reasonably well, but it did not remove all background artifacts consistently across the clip.

◐ Mixedinput + output shownTest date not recordedAuphonic
What was measured
Handling different noise types

Does the tool perform equally well on steady noise like fan hum, intermittent noise like dog barking or door slamming, and overlapping speech?

decisive for this rankingtransformation

Real recordings contain different noise patterns, so performance across hum, barking, slams, and overlapping speech is part of the main task. (3 of 3 judges)

What was given, what came back

Test input: Indoor Air Conditioner Noise · audio · group: background-noise-removal
Input — what we sent
0:00 / 0:00
Loading audio...
Indoor Air Conditioner Noise

A real-world indoor speech recording with a single continuous HVAC/air-conditioner noise source. It is designed to test speech isolation and noise reduction when the background noise is predictable and steady.

Why this input is hard
  • · Removal of continuous HVAC noise
  • · Speech preservation with steady background noise
  • · Natural voice quality retention
  • · Background noise reduction with minimal cleanup
Provenance
Observation
10fbbe5e-0fce-46a3-8d66-740f6d5349ba
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
observed
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: "auphonic",
  scenario: "background-noise-removal"
})
MCP · mcp.aidemos.com/api/mcp
Free with attribution.
Same input, same check — 4 other tools
measured on Handling different noise types
Real inputs and real outputs, no retouching · every cell queryable via API & MCP · aidemos.com