Remove Background Noise From Audio Files
FreeAI-powered background noise removal for podcasts, voiceovers, and recordings. Handles HVAC hum, traffic, keyboard clicks, and room echo. Free to try, Pro for full files.
What's next
Settings guide
Noise types and expected results:
| Noise Type | AI Removal Effectiveness | Notes |
|---|---|---|
| HVAC / air conditioning | Excellent | Steady-state tonal noise — AI identifies and removes consistently |
| Electrical hum (50/60 Hz) | Excellent | Consider EQ notch filter as a free alternative for hum-only issues |
| Keyboard / mouse clicks | Very good | Impulse noise — AI detects transient events outside speech patterns |
| Room echo / reverb | Good | Reduces echo; heavy reverb rooms retain some tail |
| Traffic (outdoor) | Good | Broadband; AI preserves speech, reduces traffic substantially |
| Wind noise | Moderate | Highly variable frequency content; results vary by severity |
| Crowd/party background | Moderate | Overlapping speech is the hardest case for AI — partial reduction |
Aggressiveness setting:
Lower aggressiveness preserves more naturalness at the cost of leaving more noise. Higher aggressiveness removes more noise but can introduce "over-processing" artefacts — voices sound slightly artificial, "swimmy," or reverberant. For most recordings, a medium setting produces the best balance.
Free alternative for hum only: The Equalizer tool's free parametric EQ can notch-filter a specific hum frequency without any credit cost. Set a narrow cut at 50 Hz (or 60 Hz for North America) and its harmonics (100, 150, 200 Hz) for basic hum reduction.
Format comparison
AI noise removal vs EQ filters: A parametric EQ reduces or eliminates audio at specific frequency bands. It is effective for narrow, predictable noise (60 Hz hum) but damages the desired signal when used on broadband noise. AI noise removal identifies noise patterns across all frequencies and removes them selectively, preserving the desired audio. For hum: EQ works fine. For everything else: AI produces substantially better results.
AI noise removal vs noise gate: A noise gate silences audio when the signal drops below a threshold — it removes the periods between words and sentences, not the noise during speech. If the background noise is constant during speech (fan running while recording), a noise gate does nothing during those moments. AI operates during the speech, not just in the gaps.
This tool vs Adobe Podcast Enhanced Speech: Adobe Podcast's AI enhancement is free for short clips via the browser and produces competitive results for voice content. LevnTools processes locally (no file upload for the free EQ path) and uses credits for the AI path. For music and non-voice audio, purpose-built audio AI tools typically outperform speech-focused tools like Adobe Podcast.
How it works
Upload
Drop your audio recording — podcast, voiceover, interview, or any file with background noise.
Select noise type
Choose the noise category for optimised processing, or use auto-detect.
Process
The AI model isolates and removes noise while preserving speech and music clarity. Credits are used for this step.
Download
Preview the cleaned audio and download. Compare before and after to confirm the result meets your needs.
About this format
Background noise in an audio recording falls into two categories: noise that occupies specific frequencies (HVAC hum at 50/60 Hz and its harmonics, electrical interference at specific bands), and noise that spans the full audio spectrum (room ambience, traffic, wind, crowd noise). The approach to removing each is fundamentally different.
Frequency-specific noise can be addressed with equalisation — identify the frequencies the noise occupies and reduce them with a narrow EQ cut. A 60 Hz notch filter removes electrical hum. The limitation is that voice and music also contain energy in those frequency ranges, so aggressive EQ cuts reduce clarity in the audio you want to keep.
Broadband noise — the noise that covers all frequencies — cannot be cut with EQ without also cutting the signal you want to preserve. This is where AI noise removal is categorically better than traditional tools. The AI model is trained on thousands of recordings of voice, music, and known noise types. It learns to distinguish the acoustic signature of speech from the acoustic signature of background noise, even when they overlap in the same frequency band.
The practical result: an HVAC hum that an EQ might reduce by 50% (at the cost of some voice warmth) an AI model can eliminate at 90%+ while leaving voice clarity intact. For broadband noise — traffic, wind, fan — AI is often the only tool that works without audible damage to the desired signal.