Think Sound | AI Video Dubbing API

ThinkSound

ThinkSound is a cutting-edge video-to-audio generation model that creates realistic sound effects and audio tracks from video content. By analyzing the visual elements and actions in your video, it generates high-quality audio that perfectly matches what's happening on screen.

Why It Stands Out

Video-to-audio generation: Converts video content into corresponding audio tracks automatically.
Context-aware sound: Analyzes visual elements and actions to generate matching audio.
Prompt-guided output: Add text descriptions to guide the style and type of audio generated.
Prompt Enhancer: Built-in AI-powered prompt optimization for better audio results.
High-quality output: Produces clear, realistic audio that enhances the multimedia experience.
Reproducibility: Use the seed parameter to recreate exact results or explore variations.

Parameters

Parameter	Required	Description
video	Yes	Source video (upload or public URL).
prompt	No	Text description to guide audio generation style.
seed	No	Set for reproducibility; -1 for random.

How to Use

Upload your video — drag and drop a file or paste a public URL.
Add a prompt (optional) — describe the type of sound you want. Use the Prompt Enhancer for AI-assisted optimization.
Set a seed (optional) for reproducible results.
Click Run and wait for audio generation.
Preview and download the result.

Best Use Cases

Video Post-Production — Add sound effects to silent footage or animations.
Content Creation — Generate audio tracks for social media videos and clips.
Game Development — Create sound effects for gameplay footage and trailers.
Film & Animation — Produce foley and ambient sounds for scenes.
Advertising — Add impactful audio to promotional videos.

Pricing

Output	Price
Per video	$0.05

Pro Tips for Best Quality

Use videos with clear visuals and distinct actions for best audio matching.
Add prompts to specify the type of sound you want (e.g., "engine roaring", "footsteps on gravel").
Ensure the video has visible sound-producing elements like movement, impacts, or environmental features.
For complex scenes, describe the primary sound you want the model to focus on.
Fix the seed when iterating to compare different prompt variations.

Notes

Ensure uploaded video URLs are publicly accessible.
Processing time varies based on video length and current queue load.
Please ensure your content complies with usage guidelines.

Think Sound API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/think-sound 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 URLs from data.outputs. Examples for Think Sound below.

HTTP example

# Submit the prediction
curl --fail-with-body --connect-timeout 10 --max-time 60 \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/think-sound" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d '{
    "video": "https://example.com/your-input.mp4",
    "seed": -1
}'

# Wait at least 2 seconds, then poll. Safe GET requests may be retried.
curl --fail-with-body --connect-timeout 10 --max-time 30 \
  --retry 4 --retry-all-errors --retry-delay 1 \
  -X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY"

# Start at 2 seconds and increase the interval for long-running tasks.
# Stop on completed, failed, cancelled, or timeout.

Node.js example

// npm install wavespeed
const { Client } = require('wavespeed');

const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');
const client = new Client(apiKey);

try {
  const result = await client.run("wavespeed-ai/think-sound", {
        "video": "https://example.com/your-input.mp4",
        "seed": -1
}, {
    timeout: 3600,
    pollInterval: 2.0,
  });
  console.log(result.outputs);
} catch (error) {
  console.error('Generation failed:', error);
  process.exitCode = 1;
}

Python example

# pip install wavespeed
import os
from wavespeed import Client

client = Client(api_key=os.environ["WAVESPEED_API_KEY"])

try:
    output = client.run(
        "wavespeed-ai/think-sound",
        {
    "video": "https://example.com/your-input.mp4",
    "seed": -1
},
        timeout=3600.0,
        poll_interval=2.0,
    )
    print(output["outputs"])
except Exception as error:
    raise SystemExit(f"Generation failed: {error}") from error

Think Sound API — Frequently asked questions

What is the Think Sound API?

Think Sound is a WaveSpeedAI model for AI inference, exposed as a REST API on WaveSpeedAI. ThinkSound turns uploaded videos into realistic, text-guided audio. Upload a video and add a text prompt to generate lifelike sound. 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 Think Sound 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/think-sound.

How much does Think Sound cost per run?

Think Sound 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 Think Sound accept?

Key inputs: `prompt`, `video`, `seed`. 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/think-sound.

How long does Think Sound take to generate?

Average end-to-end generation time on WaveSpeedAI is around 43 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.

Can I use Think Sound 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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