← 返回 Skills 市场
218
总下载
0
收藏
1
当前安装
9
版本数
在 OpenClaw 中安装
/install stt-recognizer
功能描述
语音转文字（Speech-to-Text / STT）工具。 支持从麦克风录音，使用 Whisper（faster-whisper）在本地进行语音转文字， 或通过 OpenAI 兼容 API 进行云端转写。 触发词：录音、语音转文字、STT、语音识别、转写、录音转文字。 适用平台：Linux / Windows...
安全使用建议
This skill appears to do what it says: record from your microphone and transcribe locally or via an OpenAI‑compatible API. Before installing and running it:
- If you plan to use API mode, only set STT_API_URL/STT_API_KEY for a trusted provider — audio will be uploaded to that endpoint. Keep keys secret.
- The Python requirements include torch and Whisper implementations; install in a virtualenv/conda environment rather than system Python to avoid altering system packages (the quickstart suggests --break-system-packages which can be disruptive).
- Model downloads are large (hundreds of MB to multiple GB) and will be stored under ~/.cache/huggingface/modules/stt-recognizer — ensure you have disk space and bandwidth.
- The scripts access your microphone and save recordings under ~/.openclaw/workspace/projects/stt-recognizer/recordings (privacy consideration). If you want to avoid saving raw audio, inspect/modify scripts to change behavior.
- Run the code in an isolated environment (virtualenv, container) if you do not fully trust the source, and review the included scripts (they are small and readable) before supplying credentials or running downloads.
If you want, I can extract the exact places where audio is saved and where network calls occur, or help craft a safer installation command (virtualenv + pip) and show how to run API mode without persisting raw files.
功能分析
Type: OpenClaw Skill
Name: stt-recognizer
Version: 1.0.8
The skill bundle provides legitimate Speech-to-Text (STT) functionality using the Whisper model (local or API-based). The scripts (record_audio.py, transcribe.py, and record_and_transcribe.py) perform their stated functions using standard libraries like PyAudio and faster-whisper, with no evidence of data exfiltration, malicious execution, or prompt injection.
能力标签
能力评估
Purpose & Capability
Name/description describe an STT tool. Included scripts (record_audio, transcribe, download_models, record_and_transcribe) and requirements (faster-whisper/whisper/openai, audio libraries, torch) are consistent with local transcription and optional API-based transcription.
Instruction Scope
SKILL.md and scripts instruct recording from the microphone, saving recordings under the workspace, downloading Whisper models into ~/.cache/huggingface/modules/stt-recognizer, and optionally sending audio to an OpenAI-compatible API when the user provides STT_API_URL/STT_API_KEY. These behaviors are expected for an STT skill, but note that enabling API mode transmits audio externally and the quick-start uses a system-wide pip install flag (--break-system-packages) which may modify system packages.
Install Mechanism
There is no packaged installer; the skill is instruction- and script-based. The provided download_models.sh calls faster_whisper.download_model to fetch model weights (expected behavior). This will download large model files (hundreds of MB to >1GB) into the user's cache directory and write them to disk — expected but resource-intensive. No suspicious external shorteners or unknown install URLs are used.
Credentials
No required credentials are declared in registry metadata. The skill documents optional environment variables (OPENCLAW_WORKSPACE, STT_MODEL_PATH, STT_API_URL, STT_API_KEY) that are reasonable for an STT tool. Requesting an API key only makes sense when the user opts into API mode; there are no unrelated secret requests.
Persistence & Privilege
always is false and the skill does not request elevated or global agent privileges. It writes models and outputs to user-local cache and workspace directories (normal for ML workloads) and does not modify other skills or system-wide agent config.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install stt-recognizer - 安装完成后，直接呼叫该 Skill 的名称或使用
/stt-recognizer触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.0.8
1. Fix all internal path references and display names to match the renamed stt-recognizer slug. 修复所有内部路径引用和展示名，统一为新命名的 stt-recognizer。
v1.0.7
1. Rename the skill from speech-transcriber to stt-recognizer and update the bilingual display name. 将技能从 speech-transcriber 重命名为 stt-recognizer，并更新中英文双语展示名。
v1.0.6
Fix repeated model downloads: add correct cache path to model search paths and fix find_model() to locate directories instead of files. 修复重复下载：添加正确的模型搜索路径，修复 find_model() 定位模型目录而非文件。
v1.0.5
Fix output paths from stt/ to speech-transcriber/ to match documentation
v1.0.4
1. Restructure directories: project and model cache now use skill-name convention. 优化目录结构，项目目录和模型缓存统一使用技能同名规范。
2. Update SKILL.md: paths unified to ~/.cache/huggingface/modules/speech-transcriber/. 更新 SKILL.md，路径统一为缓存位置。
3. Download script updated: default to small model. 下载脚本更新，默认下载 small 模型。
4. Clean up residual files and models directories. 清理残留旧文件和目录。
v1.0.3
Fix display name to Speech Transcriber | 语音转录器. Remove broken symlink and fix shell=True security issue. 修复显示名称；移除坏符号链接；修复安全问题。
v1.0.2
Remove broken symlink models/model.bin that caused embedding failures. Fix subprocess.run(shell=True) in record_audio.py for security compliance. 移除导致Embedding失败的坏符号链接；修复 subprocess.run(shell=True) 安全问题。
v1.0.1
Fix subprocess.run(shell=True) in record_audio.py for security compliance. 修复 record_audio.py 中 subprocess.run(shell=True) 调用，提升安全性。
v1.0.0
Initial release: Local speech-to-text with Whisper/faster-whisper and OpenAI API support. 首发版本：支持本地 Whisper 和 API 语音转文字。
元数据
常见问题
STT Recognizer | STT 识别器 是什么？
语音转文字（Speech-to-Text / STT）工具。 支持从麦克风录音，使用 Whisper（faster-whisper）在本地进行语音转文字， 或通过 OpenAI 兼容 API 进行云端转写。 触发词：录音、语音转文字、STT、语音识别、转写、录音转文字。 适用平台：Linux / Windows... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 218 次。
如何安装 STT Recognizer | STT 识别器？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install stt-recognizer」即可一键安装，无需额外配置。
STT Recognizer | STT 识别器 是免费的吗？
是的，STT Recognizer | STT 识别器 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
STT Recognizer | STT 识别器 支持哪些平台？
STT Recognizer | STT 识别器 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 STT Recognizer | STT 识别器？
由 Morois（@moroiser）开发并维护，当前版本 v1.0.8。
推荐 Skills