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Heartmula Transcribe Lyrics

wavespeed-ai /

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.

speech-to-text
Eingabe

Bereit

{
  "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"
}

$0.05pro Durchlauf·~20 / $1

BeispieleAlle anzeigen

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README

HeartMuLa Transcribe Lyrics

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

ParameterRequiredDescription
audioYesMusic audio file to transcribe (URL or upload)

How to Use

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

Pricing

OutputCost
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

Hinweis:Diese Website nutzt KI-Modelle von Drittanbietern.

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. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Heartmula Transcribe Lyrics below.

HTTP example
set -euo pipefail

: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"

REQUEST_BODY=$(cat <<'JSON'
{
    "audio": "https://interactive-examples.mdn.mozilla.net/media/cc0-audio/t-rex-roar.mp3"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/heartmula/transcribe-lyrics" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d "$REQUEST_BODY")

TASK=$(printf '%s' "$SUBMIT_RESPONSE" | jq 'if has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "$TASK" | jq -r '.id')
if [ -z "$PREDICTION_ID" ] || [ "$PREDICTION_ID" = "null" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL=$(printf '%s' "$TASK" | jq -r '.urls.get // empty')
if [ -z "$RESULT_URL" ]; then
  RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"
fi

# 2. Poll until the prediction finishes.
while true; do
  RESPONSE=$(curl --silent --show-error --fail-with-body "$RESULT_URL" \
    -H "Authorization: Bearer $WAVESPEED_API_KEY")
  RESULT=$(printf '%s' "$RESPONSE" | jq 'if has("data") then .data else . end')
  STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
  case "$STATUS" in
    completed) printf '%s\n' "$RESULT" | jq '.outputs'; break ;;
    failed|cancelled|timeout) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
    created|processing) sleep 2 ;;
    *) printf 'Unexpected status: %s
' "$STATUS" >&2; exit 1 ;;
  esac
done
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/wavespeed-ai/heartmula/transcribe-lyrics";
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');

async function requestJson(url, options = {}) {
  const response = await fetch(url, options);
  if (!response.ok) throw new Error(await response.text());
  return response.json();
}

// 1. Submit the prediction.
const body = await requestJson(submitUrl, {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "audio": "https://interactive-examples.mdn.mozilla.net/media/cc0-audio/t-rex-roar.mp3"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${task.id}/result`;

// 2. Poll until the prediction finishes.
while (true) {
  const resultBody = await requestJson(resultUrl, {
    headers: { "Authorization": `Bearer ${apiKey}` },
  });
  const result = resultBody.data ?? resultBody;
  if (result.status === "completed") {
    console.log(result.outputs);
    break;
  }
  if (["failed", "cancelled", "timeout"].includes(result.status)) throw new Error(JSON.stringify(result));
  if (!["created", "processing"].includes(result.status)) throw new Error("Unexpected status: " + result.status);
  await new Promise(resolve => setTimeout(resolve, 2000));
}
Python example
import json
import os
import time
from urllib.request import Request, urlopen

api_key = os.environ["WAVESPEED_API_KEY"]
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
payload = {
    "audio": "https://interactive-examples.mdn.mozilla.net/media/cc0-audio/t-rex-roar.mp3"
}

def request_json(url, data=None):
    request = Request(url, data=data, headers=headers, method="POST" if data else "GET")
    with urlopen(request) as response:
        return json.load(response)

# 1. Submit the prediction.
body = request_json("https://api.wavespeed.ai/api/v3/wavespeed-ai/heartmula/transcribe-lyrics", json.dumps(payload).encode())
task = body.get("data", body)
if not task.get("id"):
    raise RuntimeError("Submission response did not contain a prediction id")
result_url = task.get("urls", {}).get("get") or f"https://api.wavespeed.ai/api/v3/predictions/{task['id']}/result"

# 2. Poll until the prediction finishes.
while True:
    result_body = request_json(result_url)
    result = result_body.get("data", result_body)
    status = result.get("status")
    if status == "completed":
        print(result.get("outputs", []))
        break
    if status in {"failed", "cancelled", "timeout"}:
        raise RuntimeError(result)
    if status not in {"created", "processing"}:
        raise RuntimeError(f"Unexpected status: {status}")
    time.sleep(2)

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 result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates production-oriented Python, JavaScript, and cURL examples with timeouts, transient-error handling, and safe GET retries. 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?

Median end-to-end generation time on WaveSpeedAI is around 16 seconds per request, based on recent successful runs. Queue time varies 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.

Heartmula Transcribe Lyrics | AI Speech-to-Text API | WaveSpeedAI