Kling V1 TTS | Realistic Voice & TTS API

Kling V1 Text-to-Speech

Kling V1 TTS is a high-quality text-to-speech model that converts written text into natural, expressive audio. With multiple voice options and adjustable speed control, it produces lifelike speech perfect for voiceovers, content creation, and accessibility applications.

Why It Stands Out

Natural-sounding voices: Generate realistic speech with human-like intonation and expression.
Multiple voice options: Choose from a variety of voice profiles to match your content needs.
Speed control: Adjust speech rate to fit your pacing requirements.
Simple workflow: Just input text, select a voice, and generate audio instantly.
Cost-effective: Flat rate for short texts, scalable pricing for longer content.

Parameters

Parameter	Required	Description
text	Yes	The text you want to convert to speech.
voice_id	Yes	Voice profile to use (e.g., chat1_female_new-3).
speed	No	Speech rate multiplier (default: 1).

How to Use

Enter your text — type or paste the content you want to convert to speech.
Select a voice — choose from available voice profiles.
Adjust speed (optional) — set speech rate (lower = slower, higher = faster).
Click Run and wait for audio generation.
Preview and download the result.

Best Use Cases

Voiceovers — Create narration for videos, presentations, and tutorials.
Content Creation — Generate audio versions of articles, blogs, and scripts.
Advertising — Produce voice content for ads, promos, and announcements.
Accessibility — Convert written content to audio for visually impaired users.
E-learning — Create spoken content for courses and educational materials.
Podcasts & Audiobooks — Generate draft narration or supplementary audio.

Pricing

Text Length	Price
Up to 1000 characters	$0.10
Beyond 1000 characters	$0.10 per 1000 characters

Examples

500 characters → $0.10 (minimum)
1000 characters → $0.10
2500 characters → 2.5 × $0.10 = $0.25
5000 characters → 5 × $0.10 = $0.50

Pro Tips for Best Quality

Use proper punctuation — commas and periods help create natural pauses.
Break long content into shorter segments for better pacing.
Test different voice profiles to find the best match for your content.
Adjust speed based on content type — slower for educational, faster for energetic ads.
Avoid excessive abbreviations or special characters that may affect pronunciation.

Notes

Processing time varies based on text length and current queue load.
Please ensure your content complies with usage guidelines.

Kling v1 Tts API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/kwaivgi/kling-v1-tts 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 Kling v1 Tts below.

HTTP example

# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/kwaivgi/kling-v1-tts" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d '{
    "voice_id": "genshin_vindi2",
    "speed": 1
}'

# 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("kwaivgi/kling-v1-tts", {
        "voice_id": "genshin_vindi2",
        "speed": 1
});

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

Python example

# pip install wavespeed
import wavespeed

output = wavespeed.run(
    "kwaivgi/kling-v1-tts",
    {
    "voice_id": "genshin_vindi2",
    "speed": 1
}
)

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

Kling v1 Tts API — Frequently asked questions

What is the Kling v1 Tts API?

Kling v1 Tts is a Kuaishou model for audio generation, exposed as a REST API on WaveSpeedAI. Kling V1 TTS creates natural-sounding audio and supports KlingAI image, video, sound effect, virtual model, and custom AI workflows. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the Kling v1 Tts 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/kwaivgi/kwaivgi-kling-v1-tts.

How much does Kling v1 Tts cost per run?

Kling v1 Tts 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 Kling v1 Tts accept?

Key inputs: `speed`, `text`, `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/kwaivgi/kwaivgi-kling-v1-tts.

How long does Kling v1 Tts take to generate?

Average end-to-end generation time on WaveSpeedAI is around 7 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.

Can I use Kling v1 Tts outputs commercially?

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

ExamplesView all

Related Models

README