audio-extractor
Extract audio from video files to WAV format. Use when you need to analyze audio from video, prepare audio for energy calculation, or convert video audio to standard format for processing.
- License 许可
- Apache-2.0
- 最近更新
- 2026-04-21
- Stars
- ★ 0
- Forks
- 0
01 前言 Front Matter
- name
- audio-extractor
- description
- Extract audio from video files to WAV format. Use when you need to analyze audio from video, prepare audio for energy calculation, or convert video audio to standard format for processing.
02 资源文件 1
- 脚本scripts/extract_audio.py1.6 KB
03 SKILL.md 正文
Audio Extractor
Extracts audio from video files to WAV format for further analysis. Converts to mono 16kHz PCM format optimized for speech/energy analysis.
Use Cases
- Extracting audio for speech analysis
- Preparing audio for energy calculation
- Converting video audio to standard format
Usage
python3 /root/.claude/skills/audio-extractor/scripts/extract_audio.py \
--video /path/to/video.mp4 \
--output /path/to/audio.wav
Parameters
--video: Path to input video file--output: Path to output WAV file--sample-rate: Audio sample rate in Hz (default: 16000)--duration: Optional duration limit in seconds (default: full video)
Output Format
- Format: WAV (PCM 16-bit signed)
- Channels: Mono
- Sample rate: 16000 Hz (default)
Dependencies
- ffmpeg
Example
# Extract first 10 minutes of audio
python3 /root/.claude/skills/audio-extractor/scripts/extract_audio.py \
--video lecture.mp4 \
--duration 600 \
--output audio.wav
Notes
- Output is always mono for consistent analysis
- 16kHz sample rate is sufficient for speech analysis and reduces file size
- Supports any video format that ffmpeg can read
04 同仓库更多 Skills
data-reconciliation
暂无简介
speech-to-text
Transcribe video to timestamped text using Whisper tiny model (pre-installed).
video-processor
Process videos by removing segments and concatenating remaining parts. Use when you need to remove detected pauses/openings from videos, create highlight reels, or batch process segment removals using ffmpeg filter_complex.
silence-detector
Detect initial silence segments in audio/video using energy-based analysis. Use when you need to find low-energy periods at the start of recordings (title slides, setup time, pre-roll silence).
segment-combiner
Combine multiple segment detection results into a unified list. Use when you need to merge segments from different detectors, prepare removal lists for video processing, or consolidate detection outputs.
report-generator
Generate compression reports for video processing. Use when you need to create structured JSON reports with duration statistics, compression ratios, and segment details after video processing.