Heartmula Transcribe Lyrics

{ "lyrics": "Eyes on the prize, no time to sleep, uh In the shadows, the secrets I keep, uh Hit hard, move fast, never retreat, uh I'm the king of the concrete street Eyes on the prize, no time to sleep In the shadows, the secrets I keep Hit hard, move fast, never retreat I'm the king of the concrete street Eyes on the prize No time to sleep In the shadows, the secret sidekick Hit hard, move fast, never retreat I’m the king of the concrete street" }

HeartMuLa Transcribe Lyrics is an AI-powered audio transcription model that extracts lyrics from music tracks. Upload a song and the model automatically recognizes and transcribes the vocal content into text.

Why Choose This?

Automatic lyrics extraction Transcribes vocals from any music track into readable text.
Simple one-input workflow Just upload an audio file — no additional configuration needed.
Fast processing Get transcribed lyrics in seconds.
Versatile audio support Works with various audio formats and music styles.

Parameters

Parameter	Required	Description
audio	Yes	Music audio file to transcribe (URL or upload)

How to Use

Upload your audio — provide the music track you want to transcribe.
Run — submit and receive the transcribed lyrics.

Pricing

Output	Cost
Per transcription	$0.05

Best Use Cases

Lyrics Transcription — Extract lyrics from songs for reference or annotation.
Music Production — Transcribe vocal recordings for editing and review.
Content Creation — Get text versions of song lyrics for subtitles or captions.
Music Analysis — Extract lyrics for study, review, or documentation.
Karaoke Preparation — Generate lyrics text from audio tracks.

Pro Tips

Use high-quality audio files with clear vocals for best transcription accuracy.
Works best when vocals are prominent and not heavily mixed with instrumentals.
Combine with HeartMuLa Generate Music to create songs then verify lyrics.

Notes

Only audio is required.
Output is a JSON object containing the transcribed lyrics text.
Ensure uploaded audio URLs are publicly accessible.
Transcription accuracy depends on vocal clarity and audio quality.

Related Models

HeartMuLa Generate Music — Generate complete songs from lyrics and style tags.

Heartmula Transcribe Lyrics API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/heartmula/transcribe-lyrics with your input as JSON. The endpoint returns a prediction id; poll the prediction endpoint until status flips to completed, then read the output URL from data.outputs[0]. Examples for Heartmula Transcribe Lyrics below.

HTTP example

# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/heartmula/transcribe-lyrics" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d '{
    "audio": "https://example.com/your-audio.mp3"
}'

# Response includes a prediction id. Poll for the result:
curl -X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY"

# When status is "completed", read the output from data.outputs[0].

Node.js example

// npm install wavespeed
const WaveSpeed = require('wavespeed');

const client = new WaveSpeed(); // reads WAVESPEED_API_KEY from env

const result = await client.run("wavespeed-ai/heartmula/transcribe-lyrics", {
        "audio": "https://example.com/your-audio.mp3"
});

console.log(result.outputs[0]); // → URL of the generated output

Python example

# pip install wavespeed
import wavespeed

output = wavespeed.run(
    "wavespeed-ai/heartmula/transcribe-lyrics",
    {
    "audio": "https://example.com/your-audio.mp3"
}
)

print(output["outputs"][0])  # → URL of the generated output

Heartmula Transcribe Lyrics API — Frequently asked questions

What is the Heartmula Transcribe Lyrics API?

Heartmula Transcribe Lyrics is a WaveSpeedAI model for AI inference, exposed as a REST API on WaveSpeedAI. HeartMuLa Transcribe extracts lyrics from audio files using advanced AI. Supports multilingual transcription. Ready-to-use REST inference API with best performance, no coldstarts, and affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the Heartmula Transcribe Lyrics API?

POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID; poll the prediction endpoint until status flips to "completed", then read the output URL from the result. The playground generates a ready-to-paste code sample in Python, JavaScript, or cURL for whatever inputs you've set. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/wavespeed-ai/heartmula-transcribe-lyrics.

How much does Heartmula Transcribe Lyrics cost per run?

Heartmula Transcribe Lyrics starts at $0.050 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.

What inputs does Heartmula Transcribe Lyrics accept?

Key inputs: `audio`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/wavespeed-ai/heartmula-transcribe-lyrics.

How long does Heartmula Transcribe Lyrics take to generate?

Average end-to-end generation time on WaveSpeedAI is around 8 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.

Can I use Heartmula Transcribe Lyrics outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (WaveSpeedAI). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.

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