Audio location finder. Upload a clip and AI guesses the room, environment, or country based on acoustic cues.
Select the AI model for audio analysis. Different models may have different capabilities.
Record audio directly from your microphone
To work out where an audio clip was recorded, upload it and the AI estimates the location from acoustic cues alone: the likely environment type (small bedroom, treated studio, kitchen, car, outdoors, large hall, bathroom, cafe, street), the reasoning from reverb character, ambient noise, and frequency response, a probability of indoor versus outdoor, and geographic hints pulled from background sounds like sirens, languages, traffic patterns, wildlife, and weather. When the cues are strong enough it will venture country or region guesses, each with its own confidence level. This is the audio version of the GeoGuessr game: every room has a reverb fingerprint (a bathroom's bright slapback versus a bedroom's soft absorption), and backgrounds leak geography (European versus American siren patterns, a specific bird species, left-versus-right traffic flow). The analysis speculates confidently and openly, treating it as deduction for fun rather than surveillance-grade certainty.
Upload the clip and the AI works like an acoustic detective. Environment classification reads the reverb: decay time, early reflections, and brightness separate a tiled bathroom from a carpeted bedroom from a parking garage, while a near-total absence of reflections suggests a treated studio or open field. Frequency response analysis adds evidence, since cars boost low end and small rooms stack boxy mid resonances. The indoor-versus-outdoor call gets its own probability, based on reflection density and ambient character. Geographic analysis then mines the background: siren cadences differ by country, audible language fragments anchor a region, traffic density and horn culture carry information, and wildlife is often the strongest clue of all (many bird and insect species have tight geographic ranges). Country or region guesses follow only when cues justify them, and every conclusion carries its own confidence level.
Upload the clip and the finder deduces what it can: the environment type (bedroom, bathroom, car, cafe, street, hall), an indoor versus outdoor probability, and geographic hints mined from the background, like siren cadence, language fragments, traffic character, and wildlife. When cues are strong it ventures country or region guesses, each with its own confidence.
Reverb is a fingerprint. A tiled bathroom slaps sound back bright and fast, a furnished bedroom absorbs it, a garage rings, and frequency balance adds more evidence (cars boost bass, small rooms stack boxy resonances). The reasoning is spelled out, so you see which acoustic clue drove each conclusion.
Sometimes, when the background cooperates. European and American sirens sound different, any audible speech narrows the region fast, traffic and horn habits carry information, and a single identifiable bird or insect species can pin a continent better than anything else in the clip. With a quiet indoor recording there is little to mine, and the guesses stay appropriately vague.
It is deduction for fun, not surveillance. Environment type and the indoor versus outdoor call are usually solid because reverb physics is consistent; country guesses are speculative and confidence-labeled, and a generic quiet room could be anywhere on Earth. Expect GeoGuessr-style reasoning that is transparent about how much evidence it actually has.
Outdoor or busy-environment recordings with layered background: street ambience, a cafe, an open window. The more incidental sound leaks in, the more there is to reason from. Voice memos recorded in treated or silent rooms give the analysis almost nothing, which it will admit rather than invent.
No. The analysis works at the level of room type, environment, and at best region; it has no mechanism for street-level precision. The realistic privacy lesson runs the other way: your recordings leak more context than you think (language, sirens, birdlife), which is worth knowing before posting audio publicly.
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