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What is LALAL.AI?

The Lalal.ai tool is an AI powered stem splitter and vocal remover that can extract vocals and instruments from audio and video files. It also includes a voice cleaner that can remove unwanted noise and artifacts from audio tracks. The tool offers various packages with different levels of processing time and input/output formats. It can be used for individual and business purposes and integrates with other services through its API.

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⭐ LALAL.AI Core features

  • ✔️ Stem splitter
  • ✔️ Vocal remover
  • ✔️ Voice cleaner
  • ✔️ Audio file processing
  • ✔️ Video file processing

⚙️ LALAL.AI use case ideas

  1. Separating vocals and instruments in music production.
  2. Cleaning up audio recordings for podcasts or videos.
  3. Integrating with other audio processing services for business purposes.

🙋‍♂️ Users of this tool

Musicians
Audio editors
Podcasters
Content creators
Djs

💰 LALAL.AI Pricing

Prices are subject to change. Always verify pricing information.

Lite pack

€18

Plus pack

€25 €50 -50%

Pro pack

€35 €70 -50%

Master

€50 €100 -50%
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How do you rate LALAL.AI?

5 1 ratings

Breakdown 👇

Value for money:
5.0
Ease of Use:
5.0
Performance:
5.0
Features:
5.0
Support:
5.0
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❓ LALAL.AI FAQ

The Lalal.ai tool is an AI-powered stem splitter, vocal remover, and voice cleaner that extracts vocals and instruments from audio and video files, removes unwanted noise and artifacts, and integrates with other services through its API.
Getting started with LALAL.AI is easy! Simply visit the official website and sign up for an account to start.
LALAL.AI uses a Freemium pricing model , meaning there is a free tier along with other options.
The typical users of LALAL.AI include:
  • Musicians
  • Audio editors
  • Podcasters
  • Content creators
  • Djs
Follow LALAL.AI on social media to stay updated with the latest news and features:
LALAL.AI enjoys a popularity rating of 6.76/10 on our platform as of today compared to other tools. It receives an estimated average of 1.9M visits per month, indicating interest and engagement among users.