> ## Documentation Index
> Fetch the complete documentation index at: https://docs.magichour.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Evaluate Lip Sync for Agency and Localization Work

> Test existing speaker footage with approved voiceovers, record quality and accepted-output cost, and prepare a repeatable client delivery workflow.

For an agency localizing an existing speaker video, Magic Hour's lip-sync workflow takes a video
and replacement audio. It animates mouth movement; it does not by itself validate a translation,
approve a voice or finish the ad. If your starting asset is a still portrait, use
[Talking Photo](/tools/video/talking-photo) instead.

This is a pilot process, not a claim that Magic Hour outperforms another provider.

## Prepare one representative clip

1. Obtain permission for the footage, likeness and voice. Approve the translated script and
   replacement recording before generation. Check the current
   [terms of service](https://magichour.ai/terms-of-service): commercial use requires a paid
   subscription, credit-pack purchase or separately agreed paid usage-based arrangement, subject
   to applicable rights.
2. Start with a short, clear single-speaker segment with visible lips and stable lighting. Set the
   segment with `start_seconds` and `end_seconds` and provide enough audio for it. The
   [Lip Sync guide](/tools/video/lip-sync) lists input requirements and supported audio formats.
3. Set a small generation budget and a fixed retry allowance. Check `style.generation_mode`,
   `max_fps_limit` and current [pricing](/tools/video/lip-sync#pricing) before submitting.
4. Run the [lip-sync starter recipe](/get-started/starter-recipes) or use the
   [web workflow](https://magichour.ai/products/lip-sync) for a manual pilot. The recipe uploads
   local files, submits a project, waits and downloads the output.

## Review the delivered result

Watch the complete output with sound and compare it with the source. Review speech onset, pauses,
visible mouth closures, head turns, face texture and identity. Check duration, audio alignment and
required export settings. Record a concrete reason when you reject an output.

Keep separate cases for multiple speakers, frequent cuts, obscured mouths and larger movements.
A result on a clean single-speaker clip does not establish quality for those cases.

## Compare alternatives on the same client brief

Use the same approved input video and voiceover for each compatible configuration. Fix the clip
length, output requirements and retry budget. Record provider, model or generation mode, settings,
date and every attempt, including failures.

Use the [API evaluation scorecard](/integration/evaluating-media-apis) to calculate:

* **Accepted-output rate:** accepted outputs divided by submitted jobs.
* **Generation cost per accepted output:** all generation charges, including charged retries and
  rejected outputs, divided by accepted outputs. Leave this undefined if none are accepted.
* **Time to usable output:** submission through download and review, with operator time recorded
  separately.

For Magic Hour, record the project's `credits_charged` and convert credits using your own billing
arrangement. Do not compare one provider's credit count directly with another provider's dollar
price or treat a mock response as a quality benchmark.

## Deliver and repeat safely

Retain the project ID if polling times out and check that job before creating another. Download
successful output before its signed URL expires. Keep client media, keys and signed URLs out of
public scorecards; use permitted example assets for any public demonstration.

For batch delivery, add bounded concurrency, per-client budget tracking and an explicit review
step. Follow [production integration](/integration/adding-api-to-your-app) and
[webhook signature verification](/integration/webhook/secure-handler) for application workflows.
Re-run your matched cases when generation settings or the client brief change.


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