据 AlphaMoat 统计,截至 2026-09,Local Whisper 累计下载 4,425 次、获 0 个星标,在全部 5,078 个 AI 技能中排名第 2,199 位,在「设计创意」分类(512 个)中排名第 215 位。

累计安装

200

累计下载

4,425

星标

全站排名

#2,199

全站前 44% · 「设计创意」前 42%

平台	累计安装	累计下载	星标	评论
ClawHub ↗	34	1,280	-	-
SkillHub ↗	200	4,425	-	—

各平台的计数口径不同,统计时间不一致。

这个技能是做什么的

主文介绍将 Telegram 语音消息转写为文本，使用本地 whisper.cpp 模型，并说明所需构建工具、音频解码依赖与模型选择。

资料发布于 2026-10-27

可以用来做什么

在本地转写收到的 Telegram 语音消息

什么时候用

需要在本地处理语音而不调用付费语音服务时

示例提示词

以下是根据技能文档生成的示例,不代表实际运行结果。

为这条收到的 Telegram 语音消息生成文字稿

月度数据趋势

累计下载4,425

星标-

2026-09 起统计方法调整:同名技能按作者分别统计,并覆盖全部技能。图中虚线为调整前的月份,与之后的数据不直接比较,也不计算跨越调整的增长。

月份	累计下载	环比	星标
2026-09	4,425	—	-
2026-08	3,057	+45.6%	-
2026-07	2,100	+33.8%	-
2026-06	1,569	+16.7%	-
2026-05	1,344	—	-
2026-03	734	—	-

SKILL.md 原文

以下是作者发布的原始文件,按纯文本显示,本站未做修改或审核;其中的链接不可点击,命令请核实后再运行。抓取于 2026-10-23。

2.1 KB · ClawHub v1.0.2

---
name: whisper-cpp
description: Install and use whisper.cpp (local, free/offline speech-to-text) with OpenClaw. Supports downloading different ggml model sizes (tiny/base/small/medium/large-*) and configuring tools.media.audio to transcribe inbound voice notes without paid provider APIs.
---

# whisper-cpp (Local Whisper STT for OpenClaw)

This skill sets up **local whisper.cpp** STT for inbound Telegram voice notes.

## Dependencies

展开全部(共 93 行)


You need build tools (`git`, `cmake`, compiler toolchain) + `curl` and `ffmpeg` (to decode Telegram OGG/Opus → WAV).

## Install

From this skill directory:

```bash
bash scripts/install_whisper_cpp.sh
bash scripts/download_models.sh
bash scripts/install_wrapper.sh
bash scripts/patch_openclaw_audio.sh
```

Send a Telegram voice note to test.

## Tuning

### Model choice

This setup uses **ggml Whisper models** stored in `~/.cache/whisper`.

Common model names you can download:
- `tiny`, `base`, `small`, `medium`
- `large-v1`, `large-v2`, `large-v3` (bigger/slower, usually more accurate)

By default we download: `base` + `small`.

To download specific models:

```bash
bash scripts/download_models.sh tiny base small
```

For the OpenClaw wrapper, you can select:

```bash
OPENCLAW_WHISPER_MODEL=small openclaw-whisper-stt /path/to/audio
```

- Default language: auto-detect (`OPENCLAW_WHISPER_LANG=auto`)
- Force a language (example):
  ```bash
  OPENCLAW_WHISPER_LANG=en openclaw-whisper-stt /path/to/audio
  ```

Models are stored in: `~/.cache/whisper`.

## Cleanup (optional)

After install (whisper-cli + libs are in `~/.local/`):

```bash
bash scripts/cleanup_build.sh
```

## Troubleshooting

Confirm OpenClaw is using the wrapper:

```bash
which openclaw-whisper-stt
openclaw config get tools.media.audio.models
```

Test the wrapper directly:

```bash
openclaw-whisper-stt /path/to/audio.ogg
OPENCLAW_WHISPER_MODEL=small openclaw-whisper-stt /path/to/audio.ogg
```

Follow gateway logs while sending a Telegram voice note:

```bash
openclaw logs --follow
```

## Files

- Wrapper source: `bin/openclaw-whisper-stt.sh` (linked to `~/.local/bin/openclaw-whisper-stt`)
- OpenClaw config patcher: `scripts/patch_openclaw_audio.sh`