By SongTools.ai Editorial Team
If you can describe what a song sounds like, you can recreate its style in an AI music generator. This guide covers how to turn any audio file into a usable prompt for Suno, Udio, and other AI tools.
Anyone who has spent time with AI music generators like Suno or Udio knows the frustration: you have a sound in your head — or better yet, a reference track you love — but turning that sound into a text prompt that actually produces something similar is harder than it looks.
Writing a good AI music prompt is a skill. Vague prompts produce generic results. Too much description confuses the model. And even experienced producers often spend an hour iterating on prompts before landing on something close to the target.
The solution isn't to become a better prompt writer — it's to let the AI do it for you.
An audio-to-prompt tool works in reverse: instead of writing a description and generating audio, you upload existing audio and the AI generates a description. The output is a text prompt that characterises the key sonic and compositional elements of the track — genre, mood, tempo, instrumentation, production style, and more.
This reversal is powerful for several reasons:
- Style transfer: Upload a reference track you love, get a prompt, and feed it into Suno or Udio to generate something with a similar feel.
- Style documentation: Capture what makes your own productions sound the way they do. Useful for consistency across an album or for briefing collaborators.
- Catalog tagging: Generate accurate genre and mood descriptors for your entire library in minutes.
- Creative briefs: Use the generated prompt as a starting point for explaining a sonic direction to co-writers, session musicians, or producers.
When you upload an audio file to SongTools.ai's Generate Prompt from Audio tool, the AI analyses multiple dimensions of the track simultaneously:
Genre and sub-genre — Not just "electronic" but the specific flavor: lo-fi hip hop, dark techno, indie bedroom pop, soulful R&B, trap-influenced hip hop, and so on. The more specific the genre identification, the more useful the prompt.
Mood and emotion — The affective qualities of the track: melancholic, euphoric, tense, nostalgic, aggressive, dreamy. These descriptors translate directly into generator inputs.
Tempo and energy — BPM range and overall energy level. Fast-paced and high-energy reads differently from slow and atmospheric, even in the same genre.
Instrumentation — What instruments are present and how they're used. Layered synth pads vs. single acoustic guitar. Live drums vs. programmed drums. Prominent brass vs. subtle string accents.
Production style — The sonic fingerprint of the production: heavily compressed and saturated, clean and minimal, reverb-soaked and washed-out, punchy and in-your-face, warm and analog-sounding.
Vocal style — If vocals are present: style (melodic, rapped, spoken word), gender presentation, register, processing (dry, harmonised, heavily processed).
All of this is assembled into a single cohesive prompt that can be dropped directly into an AI music generator.
Once you have your generated prompt, the workflow for using it in AI generators is straightforward.
In Suno: Paste the prompt into the Style of Music field. If there are lyrics in your target sound, add those separately in the Lyrics field. Use the genre and mood descriptors from the first part of the prompt as your main input, and the production details as supplementary context.
In Udio: Use the prompt as your main text input. Udio responds well to detailed production descriptions — the more specific the sound design notes in your prompt, the more accurate the results tend to be.
General tips for both:
- Generate multiple variations (at least 4-6) from the same prompt before deciding it isn't working
- Shorten the prompt if results feel too scattered — sometimes less information gives the model more creative room
- Add specific artist references if you want to push toward a particular sound ("in the style of" phrasing works well in both tools)
- Use the prompt as a starting point and iterate — edit specific words to steer the sound in either direction
The style transfer use case is the most obvious, but it's not the only one.
Understanding your own music: Run your own productions through the tool. The resulting prompt tells you how the AI perceives your sound — which is often how a casual listener or algorithm perceives it too. This is useful data for understanding where you fit in the market and how to describe your music in pitches.
Spotting genre drift: If you're making an album intended to be cohesive, run each track through and compare the prompts. Significant divergence in the descriptions flags tracks that might sound out of place in the sequence.
Metadata generation: Music distribution platforms and sync licensing agencies often want detailed mood and genre tags. Use the generated prompts as a starting point for writing these tags accurately and consistently.
Stem analysis: Run isolated stems (drums only, bass only, full mix) through the tool to understand how each element contributes to the overall sonic character of the production.
Audio-to-prompt is a powerful tool, but it has real limits worth understanding.
It analyzes sonic characteristics, not musical theory. It will tell you the track sounds melancholic and features layered synths, but it won't give you the chord progression, the key signature, or the structural analysis of the song. For that, you need separate tools like a key and BPM finder or a MIDI generation tool.
Results are more accurate for well-defined genres. Tracks that blend multiple genres in unconventional ways may produce prompts that feel like a compromise between the influences rather than a precise description. In these cases, treat the output as a starting point and refine it manually.
The prompt describes how the track sounds, not what it's about. Lyrical themes, emotional narrative, and conceptual content aren't part of the audio analysis — only sonic and production characteristics.
The highest-value workflow for most producers is to build a small reference library of prompts from tracks they admire. Spend an hour uploading 10-15 reference tracks across the styles you work in, generating prompts for each, and saving them in a doc or note.
When you sit down to start a new project, browse that reference library instead of trying to describe what you want from scratch. Pick the closest prompt, load it into your generator, and use the first batch of generations to calibrate the direction.
This approach dramatically reduces the time you spend on prompt writing and gets you to usable audio sketches much faster — which means more time for the creative decisions that actually matter.
All the tools discussed in this article are available on SongTools.ai — free to explore.