Life & fun · September 1, 2026
CENSORLY
Create Automatic Clean Versions of Songs In Minutes
What it does
Make a clean version of ANY English or Spanish song in minutes. CENSORLY automatically detects and removes explicit lyrics and curse words creating broadcast-ready clean song edits while preserving the original audio quality. We use GPUs for fast processing, along with multiple backend checks, including lyric database searches, to make our automatic detection as accurate and reliable as possible while still providing comprehensive manually editing tools as for even further control.
Make a clean version of any song — English or Spanish — in minutes. CENSORLY automatically removes explicit lyrics and curse words from rap, hip-hop, reggaeton, and Latin tracks to produce a broadcast-ready clean edit with original audio quality preserved.
Upload any song and CENSORLY removes explicit lyrics — in English or Spanish — exporting a broadcast-ready clean version with the original audio quality, metadata, and album art intact. Clean edits in minutes, not hours. Every plan includes the same core tools. Subscribe for the volume you need. Auto-detects vocal language and applies a dedicated dictionary for each — including reggaeton and Latin trap profanity. 320kbps MP3 with original metadata, album art, and ID3 tags preserved. Drop-in replacement for the explicit version. Review every detected word with timestamps. Toggle words on or off, or add custom mute regions before exporting. Only the vocal track is muted. The…from censorly-edits.com
Does the same job
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- SSStreisand – Silence censorship, automate the effect2014 · github.com · ▲234
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Our team is filled with technologists and creators, and when we record and edit videos, 80% of the time is spent chopping up the video, removing silences, and picking the right takes. So we decided to build a tool that did that for you — or at least get you there most of the way! Our initial implementation is somewhat naïve and uses a user configurable silence threshold that just reads in volume levels. In the future, we’d like to use a frequency-based approach that focuses on the human voice. We’re also open to ideas, so let us know if you have any!
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