Douyin Video Transcribe

Douyin video transcription suite. Extract audio from Douyin/TikTok China videos, transcribe with Whisper, and analyze content. Supports video links, local files, and image notes. Trigger when user sends a Douyin link and asks for transcription, summary, or analysis.

Douyin Transcribe - Video Transcription Suite

A complete solution for transcribing Douyin (抖音/TikTok China) videos. Extracts audio, transcribes speech to text, and generates structured summaries.

Version History

Version	Changes
2.0.0	Modular architecture, improved workflow, browser DOM extraction
1.0.0	Initial release, basic transcription

Architecture

\
User Input (Douyin Link/File) │ ▼ ┌─────────────────────────────────────────┐ │ Workflow Orchestrator │ ├─────────────────────────────────────────┤ │ Step 1: Fetcher → Get video file │ │ Step 2: Transcriber → Extract & convert│ │ Step 3: Analyzer → Structure output │ │ Step 4: Output → Save results │ └─────────────────────────────────────────┘ \\

Core Features

• Video Fetching: Browser-based DOM extraction for CDN URLs
• Audio Extraction: ffmpeg-powered audio conversion
• Speech-to-Text: Whisper ASR with multiple model options
• Content Analysis: Auto-structured transcripts with key points
• Multi-format Support: Video links, local files, image notes

Prerequisites

Tool	Purpose	Install
curl	Download files	Built-in (Windows: \curl.exe)
ffmpeg	Audio extraction/merge	\winget install Gyan.FFmpeg\
Whisper	Transcription	\pip install openai-whisper\ or Docker
Browser	Video extraction	OpenClaw profile required

Docker Whisper (Recommended): \\ash docker run -d -p 9000:9000 --name whisper-asr onerahmet/openai-whisper-asr-webservice:latest \\

Workflow

Step 0: Input Classification

Input Type	Detection	Action
Video link (/video/)	URL pattern	Full workflow
Image note (/note/)	URL pattern	Snapshot only
Local video file	File path	Start from Step 2
Text input	Plain text	Start from Step 3

Step 1: Fetch Video

1.1 Resolve Short URL

\\ash

Windows PowerShell

curl.exe -sL -o NUL -w "%{url_effective}" "https://v.douyin.com/xxx/"

macOS/Linux

curl -sL -o /dev/null -w '%{url_effective}' "https://v.douyin.com/xxx/" \\

Output: \https://www.douyin.com/video/7616020798351871284\

1.2 Open Video Page

\
browser(action='open', profile='openclaw', url='https://www.douyin.com/video/{VIDEO_ID}') \\

Wait 10-15 seconds for page to load completely.

1.3 Extract Video URL (Browser DOM Method)

\\javascript browser(action='act', targetId='PAGE_ID', request={ "kind": "evaluate", "fn": "(() => { const entries = performance.getEntriesByType('resource'); const videoEntries = entries.filter(e => { const name = e.name.toLowerCase(); return name.includes('douyinvod') && (name.includes('.mp4') || name.includes('video')); }); if (videoEntries.length > 0) { const video = videoEntries[videoEntries.length - 1]; return { url: video.name, type: video.name.includes('.mp4') ? 'mp4' : 'dash' }; } return null; })()" }) \\

Important Notes:

• \ct\ action requires nested
  equest\ object with \kind\ and \n\
• Wrong: \rowser(action='act', fn='...')\
• Correct: \rowser(action='act', request={"kind": "evaluate", "fn": "..."})\

1.4 Download Video

\\ash curl.exe -L -H "Referer: https://www.douyin.com/" -o video.mp4 "<CDN_URL>" \\

Referer header is required, otherwise 403.

Step 2: Transcribe Audio

2.1 Extract Audio

\\ash

For MP4 videos

ffmpeg -i video.mp4 -ar 16000 -ac 1 -c:a pcm_s16le audio.wav -y

For DASH videos (need merge)

ffmpeg -i video.mp4 -i audio.mp4 -c copy merged.mp4 -y ffmpeg -i merged.mp4 -ar 16000 -ac 1 -c:a pcm_s16le audio.wav -y \\

Parameters:

• -ar 16000: 16kHz sample rate (Whisper requirement)
• -ac 1: Mono channel
• -c:a pcm_s16le: 16-bit PCM

2.2 Transcribe with Docker Whisper

\\ash curl.exe -X POST "http://localhost:PORT/asr" -F "audio_file=@audio.wav" \\

2.3 Alternative: Local Whisper

\\ash python -m whisper audio.wav --model small --language zh \\

Model Selection:

Model	Size	5-min Video (CPU)	Accuracy	Use Case
tiny	75MB	~30s	Fair	Quick preview
base	142MB	~1min	Good	Daily use
small	466MB	~3min	Better	Recommended
medium	1.5GB	~8min	Best	High accuracy

Step 3: Analyze Content

Agent processes transcript and generates:

1. Fix transcription errors

   • Correct homophones
   • Fix speaker names
   • Remove filler words

2. Structure content

   • Add paragraph breaks
   • Create sections

3. Extract key points

   • Main ideas
   • Important quotes

4. Generate tags

   • 3-5 topic tags

Step 4: Save Output

Transcript Format

\\markdown

{Title}

作者: {Author} 来源: 抖音 日期: {Date} 转录时间: {Transcription Date}

---

摘要

{Summary}

---

正文

{Transcript content with paragraphs}

---

要点

• {Key point 1}
• {Key point 2}
• {Key point 3}

---

标签

#{tag1} #{tag2} #{tag3} \\

File Naming Convention

\
{VIDEO_ID}-抖音转录.md \\

Troubleshooting

Stage	Issue	Solution
Step 1	Short URL fails	Check link completeness, remove share text
Step 1	JS returns null	Wait 15-20s and retry, increase timeout
Step 1	Download 403	URL expired, re-fetch from browser
Step 1	DASH no audio	Merge with \fmpeg -i video -i audio -c copy\
Step 2	ffmpeg not installed	\winget install Gyan.FFmpeg\
Step 2	Whisper service down	\docker start whisper-asr\
Step 2	Transcription slow	10-min video takes 15-20 min on CPU
Step 2	Poor quality	Use larger model (medium)

Image Note Handling

Image notes (/note/) don't need transcription:

\\

1. browser(action='open', profile='openclaw', url='IMAGE_NOTE_URL')
2. browser(action='snapshot')
3. Extract content from snapshot
4. Save to output directory \\

Edge Cases

• Article links (/article/): Use browser snapshot, no transcription
• Douyin AI summary: Extract from page as supplement
• Other platforms: Use yt-dlp for YouTube/Bilibili
• Live streams: Not supported

Related Modules

This skill can be extended with standalone modules:

Module	Purpose
douyin-fetcher	Video fetching only
douyin-transcriber	Audio transcription only
douyin-analyzer	Content analysis only
douyin-orchestrator	Workflow coordination

License

MIT-0 License - Free to use, modify, and redistribute.