Addressing Concerns About Suno AI Music Generation Quality

Creating viable music, especially a hit, is a challenging endeavor. Even the most talented musicians struggle to produce a few successful songs throughout their entire careers. If it were easy, artists would be churning out hits daily. Suno AI is not yet at the stage where it can replace the nuanced quality of human creativity as a final output. However, the progress made is remarkable. Consider this: generating an album's worth of songs in just two months would have been mind-blowing at the start of the year. How quickly we become spoiled!

The User’s Experience

For the past two months, the user has been creating music using Suno AI. Out of 8 songs, they generated 50 versions each, resulting in 400 tracks. Here’s the breakdown:

• Usable Versions: About 12 versions per song were deemed usable.
• Acceptable Versions: Roughly 3-5 versions per song were acceptable.
• Total Quality Tracks: Only around 30-32 tracks out of 400 were of a quality that the user found listenable.

The user emphasized that the issue is not due to a lack of expertise with prompts or AI, as they have a background in AI algorithms and music creation. The main concern is the generation quality and the usable ratio provided by Suno AI.

Understanding the Issue

The primary concern here is the efficiency and quality of AI-generated music. While AI tools like Suno AI offer innovative ways to create music, they are still evolving and may not always meet professional standards. The quality of generated content can vary based on several factors, including the complexity of the prompts, the desired style, and the inherent limitations of the AI.

Possible Solutions and Recommendations

1. Refining Prompts: While the user is experienced, continually refining and experimenting with prompts can sometimes yield better results. Small adjustments in phrasing or specifying more detailed requirements can improve the output.
2. Post-Processing: Accept that AI-generated music might require post-processing. Using digital audio workstations (DAWs) to fine-tune the AI-generated tracks can enhance their quality and make them more acceptable.
3. Community and Support: Engage with the Suno AI community for tips and shared experiences. Sometimes, other users might have discovered effective strategies for improving output quality.
4. Feedback to Suno AI: Providing detailed feedback to Suno AI can help improve future versions of the software. As AI tools are continually updated, user feedback is crucial for addressing issues and enhancing performance.
5. Hybrid Approach: Use a hybrid approach by combining AI-generated music with human creativity. Start with AI-generated ideas and then refine them manually to achieve the desired quality.
6. Exploring Alternatives: If Suno AI consistently fails to meet standards, exploring other AI music generation tools might be beneficial. Different tools have varying strengths, and another platform might better suit specific needs.

Usually, the most stubborn and hardheaded people are the ones who claim they have all the experience and knowledge required already to do the job. No, you do not. Even Einstein had to keep learning, and 99.98% of you are certainly not going to be smarter than Einstein.

Join the Discussion!

If you have similar experiences or tips to share, please join the discussion. Follow my journey with Suno AI here and share your Suno profile URLs in the comments.