Audio SRT Workflow

Use this skill for end-to-end subtitle work.

This package is self-contained for runtime entrypoints:

• - INLINECODE0
• INLINECODE1
• INLINECODE2
• INLINECODE3
• INLINECODE4

Scope

• - Mode A: audio + reference text -> aligned SRT
• Mode B: audio only -> auto subtitle SRT
• Timing QA with INLINECODE5
• Burned preview generation with INLINECODE6

Inputs To Collect First

1. 1. Audio path (wav, mp3, m4a, ...)
2. Whether a reference transcript is available
3. Output SRT path (or output directory)
4. Language hint (zh, en, ...)
5. Preferred run style: CLI, GUI, or Python API

Decision Rule

• - If transcript exists, run Mode A (align_to_srt.py --text ...).
• If transcript does not exist, run Mode B via GUI or Python API (run_auto_subtitle_pipeline).

Workflow

1. 1. Validate environment and paths.
2. Choose Mode A or Mode B by transcript availability.
3. Run subtitle generation from packaged scripts.
4. Run timing diagnostics (srt_stats.py).
5. If needed, render a preview mp4 with burned subtitles.

Resolve Skill Script Path

Set a local variable to your installed skill directory.

Codex default path:

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OpenClaw/ClawHub install path example:

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Environment Checks

Run these checks before execution:

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If faster-whisper import fails:

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Mode A Command Template (Audio + Transcript)

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Mode B Command Template (Audio Only)

GUI:

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Or use Python API in scripts:

• - Build config with INLINECODE16
• Run INLINECODE17

See command details in references/command-templates.md.

QA And Preview

Timing stats:

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Preview video:

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Output Conventions

• - Default output uses .srt extension.
• Prefer dated naming for batch runs (for example output_YYYYMMDD.srt).
• Keep intermediate checks in a separate folder from final delivery files.

Notes

• - For Chinese output (zh), the pipeline strips commas/periods only.
• If timings look off, inspect waveform snap related arguments before changing model size.
• This skill requires explicit invocation (allow_implicit_invocation: false).