Bilibili Audio Transcribe#

Convert a Bilibili link into local transcript files. Prefer this skill for Bilibili and b23.tv URLs only; do not use it for YouTube or generic web pages.

Quick start#

1. Ensure ffmpeg and ffprobe are on PATH.
2. If Python dependencies are missing, run scripts/bootstrap_env.sh or install yt-dlp and faster-whisper manually.
3. Run scripts/transcribe_bilibili.py with the target URL.
4. Return the generated transcript artifacts or summarize them if the user asked for analysis rather than raw text.

Example:

bash

python scripts/transcribe_bilibili.py "https://b23.tv/SSx810h" \
  --out-dir ./downloads/bilibili-audio \
  --model-size base \
  --beam-size 3

Workflow#

1. Validate the request#

Accept only bilibili.com or b23.tv URLs. If the URL points elsewhere, stop and say this skill is the wrong tool.

2. Prefer the bundled script#

Use scripts/transcribe_bilibili.py instead of rewriting yt-dlp / whisper glue code in the session. The script:

• downloads the best available audio
• probes audio duration with ffprobe
• transcribes with faster-whisper
• writes .txt, .srt, and .segments.json
• prints coarse ETA / progress during ASR

3. Use sensible defaults#

Default to:

• --model-size base
• --beam-size 3
• --language zh
• VAD enabled

These defaults are optimized for Chinese Bilibili speech. If the video is clearly non-Chinese or mixed-language, rerun with --language auto or a specific language code.

4. Keep outputs predictable#

By default the script writes into downloads/bilibili-audio/ relative to the current working directory. Keep all three artifacts unless the user explicitly asks for fewer outputs:

• transcript text: .txt
• subtitles: .srt
• segment metadata: .segments.json

5. Handle failures directly#

If a run fails:

• missing ffmpeg / ffprobe → install system dependency first
• missing Python packages → run scripts/bootstrap_env.sh
• extractor or redirect issues → retry with the resolved canonical Bilibili URL
• poor transcript quality → rerun with --language auto, a larger model, or --no-vad when speech is clipped

Read references/troubleshooting.md when dependency setup or extraction fails.

Resources#

scripts/#

• transcribe_bilibili.py — main downloader + ASR pipeline
• bootstrap_env.sh — create a virtualenv and install Python dependencies
• requirements.txt — Python package list for the bootstrap script

references/#

• troubleshooting.md — dependency and extraction failure playbook