# How Seedance 2.0 Handles Subtitles and Localization for Video: A Reference-Driven Workflow

> Discover how Seedance 2.0 manages subtitles and localization for video with its reference-driven architecture, separating AI plates from downstream language assets.

- Repository: [Iamemily2050 /seedance-2.0](https://github.com/Emily2040/seedance-2.0)
- Tags: api-reference
- Published: 2026-08-03

---

**Seedance 2.0 treats subtitles and localization as post-production deliverables, using a reference-driven architecture that separates clean AI-generated plates from language-specific assets produced downstream.**

Seedance 2.0 is an open-source video generation framework that enforces strict separation between AI-generated content and final localization assets. Rather than burning text into generated frames, the system produces clean, textless plates alongside structured metadata that drives post-production subtitle pipelines. This approach ensures professional delivery standards while supporting complex localization requirements including SDH captions, forced narratives, and script variants.

## The Reference-Driven Architecture

At the core of Seedance 2.0's localization strategy is the **[`references/subtitles-localization.md`](https://github.com/Emily2040/seedance-2.0/blob/main/references/subtitles-localization.md)** file. This document defines the complete subtitle pipeline as a post-production workflow rather than a generation-time feature.

The architecture mandates six distinct asset types handled separately from the AI generation:

- **Subtitles** – Translated dialogue authored from approved scripts in post-production
- **SDH captions** – Sound-cue information for accessibility, added during editing
- **Forced narrative** – Translations of on-screen signs or foreign dialogue, never burned into frames
- **Dubbing** – Alternative audio tracks
- **M&E (Music and Effects)** – Textless audio stems
- **Textless plates** – Clean versions of the footage without titles or graphics

This separation ensures that the AI model focuses exclusively on generating high-quality visual content while specialized post-production tools handle linguistic accuracy and compliance.

## Subtitle Plan Schema Integration

The project configuration schema in **[`references/json-schema.md`](https://github.com/Emily2040/seedance-2.0/blob/main/references/json-schema.md)** includes a dedicated `subtitle_plan` object that records client localization requirements during project setup. This schema validates the downstream pipeline configuration before generation begins.

The `subtitle_plan` object supports the following fields:

```json
{
  "subtitle_plan": {
    "subtitles": true,
    "sdh": false,
    "languages": ["es", "ja", "ko", "ru", "zh-Hant"],
    "reading_time_ms": 2500,
    "placement": "lower-third-safe"
  }
}

```

Validation occurs during project initialization, ensuring the pipeline knows exactly which assets to produce and which quality-control checks to apply. The `placement` field specifically guides the composition engine to maintain caption-safe areas.

## Prompt-Time Guidance for Subtitle-Friendly Footage

The [`subtitles-localization.md`](https://github.com/Emily2040/seedance-2.0/blob/main/subtitles-localization.md) reference instructs the generation model to create footage optimized for downstream captioning. Rather than generating text on screen, the model follows specific cinematographic guidelines:

- Keep dialogue short and assign clear speaker tags
- Use stable medium close-up shots to minimize motion vector complexity for caption placement
- Leave negative space in the lower third for caption insertion
- Avoid generating burnt-in text, signs, or foreign language elements that would require invasive editing

This guidance ensures that generated plates require minimal intervention before subtitle attachment.

## Handling Localization Variants

For languages with multiple script variants, Seedance 2.0 prevents naive character substitution errors through explicit vocabulary management. The **[`skills/seedance-vocab-zh/SKILL.md`](https://github.com/Emily2040/seedance-2.0/blob/main/skills/seedance-vocab-zh/SKILL.md)** file demonstrates this by separating Simplified Chinese (`zh-Hans`) from Traditional Chinese (`zh-Hant`).

The vocab file declares delivery scripts separately from prompt scripts, preventing errors such as converting `头发` (hair) to `頭髮` (Traditional) when the correct Traditional variant for "hair" is actually `頭發` in specific regional contexts. This forces the pipeline to generate distinct subtitle files for each script variant rather than attempting automatic conversion of generated content.

## Quality Control and Validation

The **[`references/delivery-qc.md`](https://github.com/Emily2040/seedance-2.0/blob/main/references/delivery-qc.md)** reference provides platform-specific quality control checks. This includes verification that footage maintains caption-safe framing according to standards like Netflix Timed Text specifications and WebVTT accessibility rules.

Additionally, the evaluation suite in **[`evals/evals.json`](https://github.com/Emily2040/seedance-2.0/blob/main/evals/evals.json)** includes a dedicated `subtitle_localization_accessibility` test. This test confirms that the model proposes a localization *plan* rather than generating final subtitles, enforcing the architectural boundary between generation and post-production.

## Implementation Examples

The following snippets illustrate how Seedance 2.0 integrates subtitle planning into the generation pipeline:

### Pipeline Skill Declaration

In [`skills/seedance-pipeline/SKILL.md`](https://github.com/Emily2040/seedance-2.0/blob/main/skills/seedance-pipeline/SKILL.md), the subtitle reference is loaded as part of the post-workflow definition:

```markdown
4. Post workflow: edit, conform, stitching, stabilization, audio cleanup,
   captions/subtitles, color, localization, versioning, textless, and delivery.

```

This line automatically pulls in [`subtitles-localization.md`](https://github.com/Emily2040/seedance-2.0/blob/main/subtitles-localization.md) and makes its guidelines available to the generation engine.

### Prompt Generation Helper

The system uses helper functions to enforce subtitle-friendly prompting:

```python
def make_subtitle_friendly_prompt(dialogue, speaker):
    # Keep sentences short, assign speaker tag, request stable framing

    return f'''
    {speaker} says: "{dialogue}"
    Shot: medium close‑up, keep background clean, leave space at bottom for captions.
    '''

```

### Post-Production Command Interface

After generation, subtitle assets are produced from the approved script:

```bash
seedance generate‑subtitles --script generated_script.txt \
    --languages es ja ko ru zh-Hant \
    --format webvtt --output ./subtitles/

```

## Summary

- **Seedance 2.0** enforces a strict separation between AI-generated footage and subtitle assets through the [`subtitles-localization.md`](https://github.com/Emily2040/seedance-2.0/blob/main/subtitles-localization.md) reference architecture.
- The **`subtitle_plan`** object in [`json-schema.md`](https://github.com/Emily2040/seedance-2.0/blob/main/json-schema.md) validates localization requirements before generation begins, specifying languages, reading times, and safe placement zones.
- The generation model creates **textless plates** with subtitle-friendly framing (stable shots, negative space) rather than embedding text.
- **Script variants** (like `zh-Hans` vs `zh-Hant`) are handled through separate vocabulary files to prevent translation errors.
- **Quality control** in [`delivery-qc.md`](https://github.com/Emily2040/seedance-2.0/blob/main/delivery-qc.md) ensures platform compliance (Netflix, WebVTT) and caption-safe framing.
- The **`subtitle_localization_accessibility`** evaluation test verifies that the system plans subtitles rather than generating them on-screen.

## Frequently Asked Questions

### Does Seedance 2.0 burn subtitles into generated video frames?

No. Seedance 2.0 explicitly prohibits burning subtitles into AI-generated frames. According to [`references/subtitles-localization.md`](https://github.com/Emily2040/seedance-2.0/blob/main/references/subtitles-localization.md), subtitles are authored in post-production from approved scripts and attached as separate SRT or WebVTT files. The model is instructed to leave space for captions but never to generate text on screen.

### How does Seedance 2.0 handle Chinese language variants in subtitles?

The system handles Simplified (`zh-Hans`) and Traditional (`zh-Hant`) Chinese through separate vocabulary declarations in [`skills/seedance-vocab-zh/SKILL.md`](https://github.com/Emily2040/seedance-2.0/blob/main/skills/seedance-vocab-zh/SKILL.md). This prevents naive character conversion errors by treating each script as a distinct delivery target with its own subtitle file, ensuring regional linguistic accuracy.

### What is the purpose of the subtitle_plan object in the JSON schema?

The `subtitle_plan` object in [`references/json-schema.md`](https://github.com/Emily2040/seedance-2.0/blob/main/references/json-schema.md) records client localization choices during project setup. It specifies which languages require subtitles, whether SDH captions are needed, target reading speeds (`reading_time_ms`), and safe placement zones. This schema is validated before generation to configure the downstream pipeline correctly.

### How does Seedance 2.0 ensure subtitle-safe framing in generated footage?

The [`subtitles-localization.md`](https://github.com/Emily2040/seedance-2.0/blob/main/subtitles-localization.md) reference provides prompt-time guidance requesting medium close-up shots with stable backgrounds and negative space in the lower third. Additionally, [`references/delivery-qc.md`](https://github.com/Emily2040/seedance-2.0/blob/main/references/delivery-qc.md) includes automated checks for caption-safe framing before final export, ensuring compliance with platform-specific safe zones.