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Openai Whisper

技能已验证活跃

Local speech-to-text with the Whisper CLI (no API key).

目的

To provide highly accurate and private speech-to-text transcription locally, without relying on external APIs or requiring an API key, by leveraging the Whisper CLI.

功能

Local speech-to-text transcription
No API key required
Leverages Whisper CLI
Supports multiple Whisper models
Configurable output formats and directories

使用场景

Transcribing audio files locally for privacy
Converting audio to text for further processing
Translating audio from other languages
Utilizing advanced speech recognition without cloud costs

非目标

Providing cloud-based transcription services
Requiring an API key for operation
Handling real-time streaming transcription (focus is on file-based processing)

Documentation

info:READMEThe README.md is very large and primarily describes the OpenClaw framework, with minimal specific information about the Whisper CLI skill itself.

安装

npx skills add steipete/clawdis

通过 npx 运行 Vercel skills CLI(skills.sh)— 需要本地安装 Node.js,以及至少一个兼容 skills 的智能体(Claude Code、Cursor、Codex 等)。前提是仓库遵循 agentskills.io 格式。

质量评分

已验证

99 /100

1 day ago 分析

信任信号

最近提交1 day ago

GitHub 所有者 steipete

星标371.6k

下载量 4.6M

许可证MIT

网站openclaw.ai

状态

查看源代码

类似扩展

Whisper

OpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast transcription, or multilingual audio processing. Best for robust, multilingual ASR.

技能

Orchestra-Research