whisperx

基于 WhisperX 的 OpenClaw 技能，在本地将音频或语音消息转写为文本，无需 API 密钥，支持 90 多种语言自动检测、词级时间戳，可选说话人分离（需 HuggingFace token）；模型首次运行时自动下载到本地缓存。

niuzb

热度 75.14

最近更新 2026-05-11 17:30:57

分类：效率依赖：代码执行 / 读写文件应用场景：文件转换 / 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 whisperx

Metadata

name: whisperX
description: WhisperX provides local speech-to-text transcription using OpenAI Whisper, with high-quality offline recognition, no API key required, word-level timestamps, and optional speaker diarization.
metadata: {"openclaw":{"emoji":"🎙️","requires":{"bins":["python3","ffmpeg"]},"install":["pip install whisperx"]}}

WhisperX Speech Recognition Skill

Local offline speech-to-text - A WhisperX-powered speech recognition skill for OpenClaw. Up to 30x faster than standard OpenAI Whisper, runs fully offline with no API key required.

Features

Pure ASR: Converts voice messages to text only — no voice replies generated
Fully offline: Model runs locally, no internet or API key needed
Word-level timestamps: Precise per-word time alignment
90+ languages: Includes auto language detection
Speaker diarization: Optional, requires a HuggingFace token

Installation

# Install ffmpeg (macOS)
brew install ffmpeg

# Install ffmpeg (Ubuntu/Debian)
apt-get install ffmpeg

# Install WhisperX
pip install whisperx
# or using uvx:
uvx whisperx

GPU users: ensure CUDA 12.8 is installed for faster inference.

Usage

# Basic transcription (auto-detect language)
whisperx path/to/audio.wav

# Specify model and language
whisperx  --model small --language zh path/to/audio.wav

# CPU mode (low memory)
whisperx --model small --device cpu --compute_type int8  path/to/audio.wav

Notes

Dependencies: whisperx, ffmpeg
Supported formats: MP3, WAV, OGG, FLAC, M4A, OPUS, AAC, and all other ffmpeg-supported formats
Model cache: Downloaded automatically to ~/.cache/whisper/ on first run
Recommended models: base or small for CPU; large-v3 for GPU