WaveSpeedAI APIWavespeed AIAce Step Audio To Audio

Ace Step Audio To Audio

Ace Step Audio To Audio

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ACE-Step Audio-to-Audio turns existing tracks into remixes or vocal edits using remix and lyrics modes while preserving audio character. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

ACE-Step — Audio to Audio 🎧

ACE-Step Audio-to-Audio is a creative music transformation model that generates new versions of existing tracks. It allows you to remix, rewrite, or restyle a song directly from an uploaded audio file — perfect for producers, remixers, and creators looking to evolve their sound.


✨ Key Features

  • 🎛 Remix Mode Change the musical style while preserving rhythm, tempo, and melodic structure. (e.g., turn a pop track into a lo-fi or EDM remix)

  • 🎤 Lyrics Mode Edit or replace the song’s vocal content while keeping the instrumental layers intact.

  • 🎚 Style Control via Tags Guide generation using genre or mood tags like “jazz,” “cinematic,” “trap,” “ambient chill.”

  • 🎵 High Fidelity Preservation Keeps fine-grained acoustic and timbral details from the original audio — ensuring professional-grade sound quality.

  • 🪄 Reproducible Outputs Use the seed parameter to reproduce or slightly vary your remix results.


🧩 Parameters

ParameterDescription
audio*Upload or link to an existing track (mp3/wav)
original_tags*Tags that describe the current genre/style
tags*Target tags for the remix (e.g., “jazz”, “rock”, “electronic”)
edit_modeChoose between remix or lyrics editing modes
original_lyrics(Optional) Input existing lyrics for contextual editing
lyrics(Optional) New or modified lyrics to be generated
seedRandomization control — use -1 for auto or set a fixed value for reproducibility

🎶 Use Cases

  • Remixing existing tracks into new genres or moods
  • Rewriting lyrics while preserving the backing music
  • Adapting songs for different campaigns, platforms, or cultural contexts
  • Creating A/B variations for music production or content testing
  • Expanding music datasets with stylistic diversity

💡 Example Workflows

1. Create a remix: Upload a pop song → set edit_mode: remix → add tags like “synthwave, retro” → generate a new version.

2. Rewrite lyrics: Upload a vocal track → choose edit_mode: lyrics → enter new lyrics → generate a rewritten version keeping rhythm and tone.


💰 Pricing

MetricPrice
Per second of generated audio$0.0002 / s

🎵 Summary

ACE-Step Audio-to-Audio transforms existing music into new creative expressions. Whether you’re remixing genres, rewriting lyrics, or refining mood and tone — it’s your all-in-one AI assistant for dynamic music evolution.

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result


# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/ace-step/audio-to-audio" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "edit_mode": "remix",
    "original_lyrics": "",
    "lyrics": "",
    "seed": -1
}'

# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"

Parameters

Task Submission Parameters

Request Parameters

ParameterTypeRequiredDefaultRangeDescription
audiostringYes--Audio file to transcribe. Provide an HTTPS URL or upload a file (MP3, WAV, FLAC up to 60 minutes).
original_tagsstringYes--Original genre tags of the audio file.
tagsstringYes--Comma-separated list of genre tags to control the style.
edit_modestringNoremixlyrics, remixEdit mode: lyrics or remix.
original_lyricsstringNo--Original lyrics of the audio.
lyricsstringNo--New lyrics for generation.
seedintegerNo-1-1 ~ 2147483647The random seed for reproducibility.

Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
data.idstringUnique identifier for the prediction, Task Id
data.modelstringModel ID used for the prediction
data.outputsarrayArray of URLs to the generated content (empty when status is not completed)
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to retrieve the prediction result
data.has_nsfw_contentsarrayArray of boolean values indicating NSFW detection for each output
data.statusstringStatus of the task: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds

Result Request Parameters

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