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Sampling Avoidance

Understanding Sampling Issues​

Users of Suno AI may encounter issues where their generated music is flagged for sampling by distribution platforms such as Tunecore. This occurs when the AI-generated content is detected as being too similar to existing copyrighted material, leading to blocked releases and potential legal issues. These detections are often automated and can sometimes be incorrect.

Strategies for Original Content​

To minimize the risk of sampling flags, it's crucial to ensure the generated music is original. Here are several strategies:

  • Original Lyrics and Compositions: Always use original lyrics and musical compositions. Avoid incorporating any pre-existing material directly, as this can be flagged as sampling. This includes avoiding direct use of melodies, chord progressions, or lyrics from existing songs.
  • Prompt Modification: Slightly alter the prompts and the AI-generated outputs. This ensures that the generated content does not closely resemble existing songs. Experiment with different phrasing, styles, and musical elements in your prompts.
  • Iterative Generation: Be persistent in your generation attempts. It may take several tries for the AI to produce completely original content. If an initial output is too similar to existing material, modify the prompt and try again.

Addressing Incorrect Claims​

If a song is incorrectly flagged for sampling, you can dispute the claim. Many times, these detections are automated and can be resolved through a human review process. This may involve providing additional information or evidence to support your claim of originality.

Licensing and Rights​

Ensure you have the proper licenses for any content you are using that is not originally yours. For Suno AI-generated music, this means understanding the licensing terms provided by Suno AI. Typically, a Pro account grants the necessary permissions to distribute the music commercially.

When facing copyright claims, providing proof of licensing and ownership is essential. Here are some examples of documentation that can be used:

  • Pro Account Status: Provide screenshots of your Pro account status on Suno, which includes licensing permissions. This demonstrates your right to distribute the music commercially.
  • Terms of Use: Show the terms of use or licensing agreements from Suno AI. This clarifies the rights granted to you for the music generated under your account.
  • Account Matching: Demonstrate the connection between your Suno account and your distributor or streaming platform account. This helps clarify that the music was generated under your licensed account.

Additional Tips​

  • Backup Documentation: Always keep a backup of all documents proving your rights to the music.
  • Engage with Support: Engage directly with your distributor’s support to discuss specific claims and seek clarification on flagged content.
  • Challenge False Positives: Be prepared to challenge false positives by disputing them directly on the distribution platform.

Platform Variations​

Be aware that different platforms may have varying algorithms for detecting AI-generated content. Some platforms may have stricter detection methods than others. Sharing experiences from other users can provide insights into platform-specific challenges and solutions.

Suno v3.5 Considerations​

The Suno v3.5 release has brought improvements in audio quality, but users should be aware of potential issues that may impact sampling concerns:

  • Longer Generation Times: The update may result in longer generation times, which can be a tradeoff for better quality.
  • Obscure Styles: Generating obscure music styles may be challenging, often resulting in basic or unrelated styles instead.
  • Genre Inaccuracy: The new version may sometimes ignore specified musical styles and genres, producing generic pop songs regardless of prompts.
  • Vocal Quality: Despite improvements, vocal quality issues like distortion and "demon choir" effects may still be present.
  • Prompt Generator Glitches: The prompt generator may occasionally fail to retain previous prompts, requiring users to add punctuation to correct the issue.
  • Pop-Washed Outputs: Users attempting to create various genres, such as metal, may end up with songs that sound overly poppy.

To mitigate these issues, users should use detailed prompts, specify genres in both the style box and within brackets at the start of the track, dispute incorrect generations, and experiment with different prompt structures.