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Audio SRT Workflow

提供音频字幕端到端流程:有参考文本时把音频与文本对齐生成 SRT(Mode A),仅有音频时自动生成字幕(Mode B);另用 srt_stats.py 做时间轴质检、make_preview_mp4.py 渲染烧录字幕的预览视频。需 Python 3.10+、ffmpeg 与 faster-whisper,需显式调用。

sariel2018
sariel2018
热度 46.94
最近更新 2026-05-11 17:38:40
分类:效率依赖:代码执行 / 读写文件应用场景:文件转换 / 视频编辑 / 自动化脚本 / 数据处理

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add audio-srt-workflow
Metadata
name
audio-srt-workflow
description
Generate or align SRT subtitles from audio using this repository. Use when the user asks for subtitle generation, transcript-to-audio alignment, timing cleanup, SRT quality checks, or subtitle preview video rendering.
license
MIT
compatibility
Requires Python 3.10+, ffmpeg in PATH, and faster-whisper runtime support.
metadata
{"owner":"Sariel2018","repository":"audio-srt-aligner"}

Audio SRT Workflow

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

This package is self-contained for runtime entrypoints:

  • scripts/align_to_srt.py
  • scripts/gui_app.py
  • scripts/srt_stats.py
  • scripts/make_preview_mp4.py
  • scripts/requirements.txt

Scope

  • Mode A: audio + reference text -> aligned SRT
  • Mode B: audio only -> auto subtitle SRT
  • Timing QA with srt_stats.py
  • Burned preview generation with make_preview_mp4.py

Inputs To Collect First

  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. 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:

SKILL_DIR="${CODEX_HOME:-$HOME/.codex}/skills/audio-srt-workflow"

OpenClaw/ClawHub install path example:

SKILL_DIR="<your-workdir>/skills/audio-srt-workflow"

Environment Checks

Run these checks before execution:

python3 --version
ffmpeg -version
python3 -c "import faster_whisper; print('ok')"

If faster-whisper import fails:

# Review dependencies before installing:
cat "$SKILL_DIR/scripts/requirements.txt"
pip install -r "$SKILL_DIR/scripts/requirements.txt"

Mode A Command Template (Audio + Transcript)

python3 "$SKILL_DIR/scripts/align_to_srt.py" \
  --audio "<input_audio>" \
  --text "<transcript_txt>" \
  --output "<output_srt>" \
  --model small \
  --language zh

Mode B Command Template (Audio Only)

GUI:

python3 "$SKILL_DIR/scripts/gui_app.py"

Or use Python API in scripts:

  • Build config with build_alignment_config(...)
  • Run run_auto_subtitle_pipeline(...)

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

QA And Preview

Timing stats:

python3 "$SKILL_DIR/scripts/srt_stats.py" --srt "<output_srt>"

Preview video:

python3 "$SKILL_DIR/scripts/make_preview_mp4.py" \
  --audio "<input_audio>" \
  --srt "<output_srt>" \
  --output "<preview_mp4>"

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).