ElevenLabs Eleven-V3 Timing converts text to natural speech and returns alignment metadata—character/word timestamps in JSON—for precise subtitles, karaoke effects, and lip-sync. Supports voice_id, similarity/stability, and optional Speaker Boost. Priced at $0.10 per 1,000 characters. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing.
En attente
{
"audio": "https://d1q70pf5vjeyhc.cloudfront.net/predictions/1298dfeb67a04c7fa1bac264734c41a9/1.mp3",
"alignment": {
"characters": [
"W",
"e",
"l",
"c",
"o",
"m",
"e",
" ",
"t",
"o",
" ",
"o",
"u",
"r",
" ",
"a",
"d",
"v",
"a",
"n",
"c",
"e",
"d",
" ",
"t",
"e",
"x",
"t",
"-",
"t",
"o",
"-",
"s",
"p",
"e",
"e",
"c",
"h",
" ",
"s",
"y",
"s",
"t",
"e",
"m",
"!",
" ",
"E",
"x",
"p",
"e",
"r",
"i",
"e",
"n",
"c",
"e",
" ",
"h",
"i",
"g",
"h",
"-",
"q",
"u",
"a",
"l",
"i",
"t",
"y",
" ",
"v",
"o",
"i",
"c",
"e",
" ",
"s",
"y",
"n",
"t",
"h",
"e",
"s",
"i",
"s",
" ",
"w",
"i",
"t",
"h",
" ",
"n",
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"a",
"r",
"t",
"i",
"c",
"u",
"l",
"a",
"t",
"i",
"o",
"n",
"."
],
"character_end_times_seconds": [
0.045,
0.09,
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0.474,
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9.09
],
"character_start_times_seconds": [
0,
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0.135,
0.18,
0.225,
0.27,
0.315,
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0.421,
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8.29,
8.37,
8.45,
8.53,
8.61,
8.69,
8.77,
8.85,
8.93
]
},
"normalized_alignment": {
"characters": [
"W",
"e",
"l",
"c",
"o",
"m",
"e",
" ",
"t",
"o",
" ",
"o",
"u",
"r",
" ",
"a",
"d",
"v",
"a",
"n",
"c",
"e",
"d",
" ",
"t",
"e",
"x",
"t",
"-",
"t",
"o",
"-",
"s",
"p",
"e",
"e",
"c",
"h",
" ",
"s",
"y",
"s",
"t",
"e",
"m",
"!",
" ",
"E",
"x",
"p",
"e",
"r",
"i",
"e",
"n",
"c",
"e",
" ",
"h",
"i",
"g",
"h",
"-",
"q",
"u",
"a",
"l",
"i",
"t",
"y",
" ",
"v",
"o",
"i",
"c",
"e",
" ",
"s",
"y",
"n",
"t",
"h",
"e",
"s",
"i",
"s",
" ",
"w",
"i",
"t",
"h",
" ",
"n",
"a",
"t",
"u",
"r",
"a",
"l",
" ",
"p",
"r",
"o",
"n",
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"c",
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"a",
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"n",
" ",
"a",
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"d",
" ",
"c",
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"e",
"a",
"r",
" ",
"a",
"r",
"t",
"i",
"c",
"u",
"l",
"a",
"t",
"i",
"o",
"n",
"."
],
"character_end_times_seconds": [
0.045,
0.09,
0.135,
0.18,
0.225,
0.27,
0.315,
0.368,
0.421,
0.474,
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0.634,
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1.06,
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1.369,
1.465,
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1.952,
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3.62,
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3.902,
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8.61,
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],
"character_start_times_seconds": [
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}
}$0.1par exécution·~10 / $1
ExemplesTout voir
Modèles associés
README
ElevenLabs — Eleven V3 TTS with Alignment
Eleven V3 (Alignment) turns text into natural speech and, at the same time, returns precise timing data for every character and word. You get an audio file plus alignment metadata, so you can drop the voice straight onto a timeline for subtitles, karaoke, lip-sync and fine-grained editing.
🎧 What this model does
- Generates high-quality speech with natural pronunciation, pacing and intonation.
- Returns alignment metadata with per-character / per-word timestamps (start–end in seconds).
- Makes it easy to build auto-subtitles, word-highlighting, reading trainers, talking avatars and precise dubbing tools.
Compared with a normal TTS model (audio only), this version also outputs an alignment object containing, for example:
- a list of characters or words
- corresponding end times in seconds (and, where available, start times)
so the text and audio are tightly locked to each other.
🧩 Typical uses
- Automatic subtitle generation with timecodes (SRT / VTT).
- Word-by-word highlighting or karaoke-style lyrics.
- Lip-sync for digital humans or 2D/3D characters driven by word/phoneme timing.
- Precise VO replacement and edit point detection inside existing videos.
- Language-learning apps: follow-along reading, shadowing and pronunciation practice.
🔧 Input parameters
-
text (required) – Script to be spoken. Recommended up to 5,000 characters per call.
-
voice_id (required) – Which Eleven voice to use (for example: Alice, Elli, George).
-
Full voice list to find your voice_id.
-
similarity (0–1) – How closely the output should match the base voice’s timbre and style.
-
stability (0–1) – Higher values give more consistent delivery; lower values allow more expressive variation.
-
use_speaker_boost (bool) – English text normalisation that improves numbers, dates and measurements.
📤 Output format
Each run returns:
-
audio – URL of the generated audio file (MP3).
-
alignment – JSON metadata including:
-
list of characters and/or words in order
-
corresponding timing arrays (for example character_end_times_seconds) with values in seconds
You can parse this metadata to:
- build subtitles with exact in/out times
- drive on-screen highlighting in sync with the audio
- control animation, lip-sync or visual effects based on specific words
💰 Pricing
Billing is based on the length of the input text.
- Base rate: 0.10 USD per 1,000 characters
- The character count is rounded up to the next 1,000 characters. Input less than 1000 characters will be charged as 1000 characters.
Anything below 1,000 characters is still billed as one full 1,000-character block.
🚀 How to use
- Fill text with your script.
- Select a voice_id from the supported ElevenLabs voices.
- Optionally tune similarity, stability, and enable use_speaker_boost for English number-heavy content.
- Run the request.
- Download the audio file and read the alignment JSON to build subtitles, highlights or animation timing.
📝 Notes and tips
- Punctuation matters: clear sentence boundaries improve rhythm and alignment accuracy.
- For very long scripts, split them into several calls if you need section-level control on the timeline.
- If you see errors like “invalid voice id”, cross-check with the most recent voice list and update the parameter value.
- When building players or editors, always treat the alignment timings (in seconds) as the single source of truth for where each character or word should appear.
Eleven v3 Timing API — Quick start
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/elevenlabs/eleven-v3/timing 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 Eleven v3 Timing below.
HTTP example
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"text": "A clear example input",
"voice_id": "Alice",
"similarity": 1,
"stability": 0.5,
"use_speaker_boost": true
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/elevenlabs/eleven-v3/timing" \
-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
doneNode.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/elevenlabs/eleven-v3/timing";
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 ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"text": "A clear example input",
"voice_id": "Alice",
"similarity": 1,
"stability": 0.5,
"use_speaker_boost": true
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
`https://api.wavespeed.ai/api/v3/predictions/${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 = {
"text": "A clear example input",
"voice_id": "Alice",
"similarity": 1,
"stability": 0.5,
"use_speaker_boost": True
}
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/elevenlabs/eleven-v3/timing", 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)Eleven v3 Timing API — Frequently asked questions
What is the Eleven v3 Timing API?
Eleven v3 Timing is a ElevenLabs model for audio generation, exposed as a REST API on WaveSpeedAI. ElevenLabs Eleven-V3 Timing converts text to natural speech and returns alignment metadata—character/word timestamps in JSON—for precise subtitles, karaoke effects, and lip-sync. Supports voice_id, similarity/stability, and optional Speaker Boost. Priced at $0.10 per 1,000 characters. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing. You can call it programmatically or try it from the playground above.
How do I call the Eleven v3 Timing 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/elevenlabs/elevenlabs-eleven-v3-timing.
How much does Eleven v3 Timing cost per run?
Eleven v3 Timing starts at $0.10 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 Eleven v3 Timing accept?
Key inputs: `similarity`, `stability`, `text`, `use_speaker_boost`, `voice_id`. 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/elevenlabs/elevenlabs-eleven-v3-timing.
How long does Eleven v3 Timing take to generate?
Median end-to-end generation time on WaveSpeedAI is around 4 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 Eleven v3 Timing outputs commercially?
Commercial usage rights depend on the model's license, set by its provider (ElevenLabs). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.