A comprehensive toolkit for generating, aligning, and validating SRT subtitles from audio files using faster-whisper and ffmpeg.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install audio-srt-workflow
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install audio-srt-workflow using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Audio SRT Workflow?
The Audio SRT Workflow is a specialized suite of tools designed for end-to-end subtitle production and synchronization. By leveraging the power of Openclaw Skills, this package enables developers and content creators to bridge the gap between raw audio and frame-perfect subtitles. It provides robust support for both transcript-based alignment and fully automated speech-to-text generation.
Built on top of the efficient faster-whisper runtime, the skill ensures high-performance processing while maintaining strict control over subtitle quality. Whether you are managing a single m4a file or batch-processing large media libraries, this skill provides the necessary CLI, GUI, and API interfaces to streamline your transcription pipeline.
Audio SRT Workflow Use Cases
- Synchronizing existing text transcripts with audio files for perfect timing.
- Auto-generating subtitles for videos and podcasts without a pre-existing script.
- Performing Quality Assurance (QA) on existing SRT files to detect timing overlaps or errors.
- Creating burned-in subtitle preview videos for quick review cycles.
- Integrating automated subtitle generation into larger media processing workflows.
How Audio SRT Workflow Works
- Environment Validation: The system verifies the presence of Python 3.10+, ffmpeg, and the faster-whisper runtime.
- Mode Selection: Based on user input, it determines whether to perform Mode A (alignment with transcript) or Mode B (automatic transcription).
- Subtitle Processing: The tool runs the core scripts to generate or align the SRT file based on the specified language hint.
- Diagnostic Check: The srt_stats script analyzes the generated file for timing consistency and technical accuracy.
- Preview Rendering: Optionally, the workflow utilizes ffmpeg to produce an MP4 preview with the subtitles burned into the video.
Audio SRT Workflow Setup
To get started with this Openclaw Skills package, ensure your environment is ready:
# Check prerequisites
python3 --version
ffmpeg -version
# Set skill directory
SKILL_DIR="${CODEX_HOME:-$HOME/.codex}/skills/audio-srt-workflow"
# Install dependencies
pip install -r "$SKILL_DIR/scripts/requirements.txt"
For basic alignment using a transcript:
python3 "$SKILL_DIR/scripts/align_to_srt.py" \
--audio "path/to/audio.wav" \
--text "path/to/transcript.txt" \
--output "path/to/output.srt" \
--language en
Audio SRT Workflow Data Schema & Taxonomy
The skill follows a structured output convention to ensure data integrity across various workflows:
| File Type | Extension | Description |
|---|---|---|
| Subtitle | .srt | The primary output containing synchronized text and timestamps. |
| Preview Video | .mp4 | Generated media with burned-in subtitles for visual verification. |
| Statistics | Console/Log | Technical metadata regarding subtitle density and timing overlaps. |
Users are encouraged to use dated naming conventions (e.g., output_20260510.srt) and maintain a clear separation between intermediate artifacts and final delivery files.
Audio SRT Workflow Advanced Features
- Multi-mode operation allowing for both GUI-based interaction and headless CLI automation.
- Language-specific processing, such as specialized punctuation handling for Chinese (zh) outputs.
- Waveform snap adjustments to fine-tune subtitle synchronization without increasing model overhead.
- Seamless integration with the Openclaw Skills ecosystem for multi-agent media pipelines.
- Automated timing diagnostics via srt_stats to ensure broadcast-quality results.
SKILL.md
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