For creators & broadcasters

Remove profanity.
Keep your voice.

Bleeper is an audio censorship engine that works at the single-word level. It strips ambient noise and isolates a clean vocal for detection. Drop in a podcast, interview, music video or track β€” you get back a broadcast-clean master without artificial auto-tune and without touching your vocal timbre.

Used by independent podcasters, YouTube studios and TV production teams across EU.

97%
word-level detection accuracy on mixed PL/EN material
< 2 min
typical turnaround on a 60-min podcast episode
MP3 Β· WAV Β· MP4 Β· MOV
lossless export with timestamped SRT
LIVE
interview_final.mp4 Β· vocal stem0:00/01:14
→…and honestly that fucking song was the best thing that happened to the whole damn show…
0:00
01:14
2 profanities detected
Fig. 01 β€” Word-level detectionv4.1 Β· real-time preview
One engine, two systems

One engine. Two production realities.

01 Β· Creators

Ship clean cuts without losing momentum.

Upload, review, publish. No plugin chain, no stems, no re-recording. Bleeper gives you a monetisable master while you stay in editing flow β€” so a Friday podcast drop still goes out on Friday.

  • YouTube, TikTok & podcast-ready
    Keep ad revenue intact without losing performance or cadence.
  • Drop-in upload, 2-click review
    No stems, no Premiere sidechain, no extra render pass.
  • Clean masters + SRT in one export
    Subtitles carry [***] markers so captions stay truthful.
  • Pay per project, not per seat
    Top up tokens when you need them. No monthly lock-in.
For creators
02 Β· Broadcasters

Pre-air compliance without a post-house.

Designed from inside a TV transmission chain β€” Bleeper fits between ingest and playout. Deterministic output, word-level logs and a desktop binary for air-gapped editorial rooms.

  • Deterministic masters with audit log
    Every muted word recorded with timestamp, confidence and source.
  • Desktop build for on-prem workflows
    Runs locally on studio hardware β€” no media leaves the facility.
  • PL + EN with studio-grade accuracy
    Wav2Vec2 tuned on Polish broadcast speech, WhisperX alignment on top.
  • Integrates with Dalet, Avid & Adobe
    AAF, OMF and broadcast-WAV in/out β€” slots into existing NLE chains.
Talk to our team
✦ AI-POWERED CONTENT CENSORSHIP

Automated content censorship in minutes

Multi-thread process for music, podcasts, interviews, and more.
Exported MP4 clip β€” broadcast ready.

πŸ‡΅πŸ‡± Polish Β· πŸ‡¬πŸ‡§ English β€” automatic language detection

✦ Based on TV broadcast experience

🎬 Process Demo
🎬
Interview_Final.mp4
18.4 MB β€’ 02:14
Analysis & Identification
AI Vocal Separation
Inappropriate Word Detection
Censorship & MP4 Export
PIPELINE

Six stages. One master.

input:.mp3.wav.mp4.mov→output:.mp4.srt

Each stage has a fail-safe fallback β€” if one source fails, the system automatically pulls from the next. No stuck jobs, no half-rendered files.

  1. 01

    Content Identification

    Automatic recognition of title, artist, and language from a short audio fragment

    Music IDLanguage detection
  2. 02

    Vocal Isolation

    Separation of vocal track from background music with studio accuracy β€” each word is analyzed separately

    Stem separationVocal isolation
  3. 03

    Lyrics Retrieval

    Automatic search and verification of text from multiple sources β€” system evaluates match quality

    Lyrics matchingMulti-source
  4. 04

    Transcription & Alignment

    Speech-to-text conversion with exact timestamp assignment for every word in the recording

    Speech-to-textWord-level timing
  5. 05

    Profanity Detection

    Triple-pass search for forbidden content β€” catches mumbled or distorted words

    Profanity detectionCustom dictionaries
  6. 06

    Censorship & Export

    Precise muting of detected fragments on the audio track and rendering the final video file

    Audio maskingVideo re-mux

failover enabled Β· every stage has a fallback source

PRICING

Simple Token Model

Subscription provides a monthly token pool. Top up anytime.

01

Starter

$8.99/mo.
1,400 tokens / monthβ‰ˆ 11 min
  • 1,400 tokens/month
  • 3 simultaneous projects
  • Max 25 MB / file
  • Transcription + detection
  • SRT export (250 tok./file)
  • Watermark
  • Priority GPU
Choose Starter
02β˜… MOST POPULAR

Basic

$14.99/mo.
3,400 tokens / monthβ‰ˆ 28 min
  • 3,400 tokens/month
  • 8 simultaneous projects
  • Max 200 MB / file
  • Cheap SRT export (15 tok.)
  • Remove watermark (βˆ’240 tok.)
Choose Basic
03

Pro

$29.99/mo.
8,000 tokens / monthβ‰ˆ 66 min
  • 8,000 tokens/month
  • 20 simultaneous projects
  • Max 1 GB / file
  • Full functionality
  • No watermarks
  • Highest GPU priority
Choose Pro
+ top-upNeed more tokens? Top up anytime:
500 tokens$4.99
2,000 tokens$12.99β˜… BEST
10,000 tokens$34.99
Flexibility

Two ways to use

Cloud for creators. Desktop for TV stations and studios.

01 Β· Cloud / SaaSOnline / Cloud

Pay only for what you process

Tokens never expire β€” they roll over to the next month (max 2Γ— monthly pack). GPU processing β€” results in minutes.

DashboardTranscriptionSRT subtitlesTimelineJSON exportMP4 export
Token Calculator1200 tokens
$8.99
/month β€” plan Starter
β‰ˆ 10β€²
min. processing
Start free
02 Β· Desktop / On-premDesktop / Enterprise

Your GPU. Your data. No cloud.

Annual workstation license. Local processing β€” zero data in the cloud. Perfect for TV stations and post-production studios.

  • Unlimited local clips
  • AI model updates for one year
  • Regulatory compliance β€” audit logs
  • Local application with graphical interface (GUI)
Annual License
599USD net + Tax
/ station / year
β†’One-time online activation
β†’48h email support
β†’AI updates included
Learn more β†’
Proven in action

Creators choose peace of mind

Join creators who automated content censorship and freed themselves from demonetization.

I used to spend up to 3 hours manually searching for and muting profanity in my YouTube videos. Since I started using Bleeper, AI censorship does it in 2 minutes. The yellow dollar is completely gone, and I got my time back for editing.

Kamil
YouTube Commentary Creator

TikTok's algorithm was cutting my reach for background profanity etc. Manually bleeping swear words was a nightmare. Now I just drop the file into Bleeper and in 30 seconds I have a guidelines-compliant video, ready to publish.

Maciek
TikTok / Reels Creator

As a podcaster, I often quote harsh material. Unfortunately, crude word-cutting was ruining the flow of entire episodes. The algorithm applies the 'bleep' so precisely to the vocal track that the podcast still sounds incredibly professional.

Anka
True Crime Podcast Host
FAQ

Frequently Asked Questions

6 questionsΒ·need more? kontakt@bleeper.eu
  1. Bleeper uses advanced AI models to analyze the audio track. The algorithm detects profanities with millisecond precision and applies a 'beep' or mute without destroying the rest of the audio.
  2. Creator privacy is our priority. After processing and downloading, your original materials are encrypted and securely deleted from our servers after 24 hours.
  3. It's up to you! In export settings, you can choose the classic 'bleep' signal or a discrete total mute, which works great for professional formats.
  4. Yes. Our AI engine is trained on modern language nuances, including slang, internet speak from streams, and distorted speech. Supports multiple languages.
  5. Our AI engine uses advanced vocal isolation. The model 'understands' the voice independently of the background music, allowing for precise censorship without creating 'holes' in the soundtrack.
  6. Yes, in Basic and Pro plans, you can export a full SRT transcription with already censored words, further speeding up your editing process.
Worth knowing

Knowledge Base & Blog

View all β†’
  1. 01Β·Insights

    How AI is changing video editing in 2026?

    Learn how automated speech detection reduces post-production time by 80%...

    Read more β†’ β†’
  2. 02Β·Insights

    Video Censorship on YouTube – How to avoid demonetization?

    A practical guide on blocked words and how Bleeper helps maintain your reach.

    Read more β†’ β†’
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