Article TTS Skill

---

name: article-tts

description: "拍照或文字转音频：文章照片 OCR 提取文字，或直接接收文字，生成 Microsoft Edge TTS 语音，支持中英文、自动转写、语速调节、逐句拆分。| Capture article photos (OCR) or plain text, generate natural audio via Edge TTS. Bilingual support (EN/ZH), configurable speed, voice, and sentence splitting."

requires:

binaries:

- tesseract # OCR engine

- uvx # uvx runner (from uv package)

- edge-tts # Microsoft Edge TTS (via uvx, no install needed)

runtime:

- python3 (with PIL/Pillow)

- tessdata (language models)

install: |

# Install Tesseract OCR + Chinese language pack

apt-get update && apt-get install -y tesseract-ocr tesseract-ocr-chi-sim

# English language pack is included by default

# If needed: apt-get install tesseract-ocr-eng

# uvx / uv will auto-download edge-tts on first run (no manual install)

credentials:

# OpenClaw handles channel authentication via its own plugin system.

# The agent will automatically detect which channel is active and use

# the appropriate credentials already configured in OpenClaw.

# No extra env vars needed — the skill just calls message(...).

#

# Supported channels (via OpenClaw message tool):

# feishu — Feishu bot (app_id/app_secret from Feishu Open Platform)

# telegram — Telegram bot (bot token from BotFather)

# discord — Discord bot (bot token + guild)

# whatsapp — WhatsApp Business API / linked device

# signal — Signal (phone number + signal-cli)

# imessage — iMessage (via macOS/icloud)

# openclaw-weixin — WeChat Work / 个人微信

#

# If the target channel is not configured, the skill saves files locally

# and notifies the user of the output path.

---

# Article TTS Skill

Default Configuration

| 参数 | 默认值 | 说明 |

|------|--------|------|

| `lang` | `en` | 语言：`en` 或 `zh` |

| `skipConfirmation` | `false` | 是否跳过文字确认步骤 |

| `speed` | `90%` | TTS 语速（`--rate=-10%` = 90%） |

| `voice` | `en-US-EmmaNeural`（英文）/ `zh-CN-XiaoxiaoNeural`（中文） | TTS 声音 |

| `splitSentences` | `false` | 是否生成按句拆分的音频 |

Supported Languages

| 语言 | OCR 语言包 | TTS Voice |

|------|-----------|-----------|

| `en` | `eng`（预装） | `en-US-EmmaNeural` |

| `zh` | `chi_sim`（需安装） | `zh-CN-XiaoxiaoNeural` |

> **中文 OCR 语言包安装：**

> - Linux（WSL/Debian/Ubuntu）：`apt-get install tesseract-ocr-chi-sim`

> - macOS：`brew install tesseract-lang`（自带中文）

> - Windows：下载 `chi_sim.traineddata` 放入 Tesseract 安装目录的 `tessdata` 文件夹

Workflow

Input Types

Standard Flow（默认，需确认）

图片 → OCR 提取文字 → 展示给用户确认 → 用户确认 → 生成 TTS → 发送
文字 → 直接生成 TTS → 发送

Skip-Confirmation Flow ⚠️

用户说"不需要确认"或"直接生成"时，跳过确认步骤。

> **⚠️ 安全提示**：skipConfirmation 会跳过文字确认步骤，OCR 提取的文本（可能包含敏感信息）会直接转为音频并发送。适用于可信来源、低敏感内容。建议默认关闭（`skipConfirmation: false`）。

OCR Step

# 图片预处理
from PIL import Image, ImageOps
img = Image.open(image_path)
img = ImageOps.autocontrast(img.convert('L'), cutoff=10)
w, h = img.size
img = img.resize((w*4, h*4), Image.LANCZOS)
img.save('/tmp/ocr_input.jpg', quality=99)

# 英文
tesseract /tmp/ocr_input.jpg stdout -l eng --psm 4

# 中文
tesseract /tmp/ocr_input.jpg stdout -l chi_sim --psm 4

TTS Step

全文字频

uvx edge-tts \
  -t "FULL TEXT" \
  -v en-US-EmmaNeural \
  --rate=-10% \
  --write-media OUTPUT_DIR/full_article.mp3

# 中文
uvx edge-tts \
  -t "中文文字内容" \
  -v zh-CN-XiaoxiaoNeural \
  --rate=-10% \
  --write-media OUTPUT_DIR/full_article.mp3

按句拆分（仅 splitSentences=true）

import subprocess, re

def split_sentences(text, lang='en'):
    if lang == 'zh':
        # 中文按句号/感叹号/问号拆分
        sentences = re.split(r'(?<=[。！？])\s*', text)
    else:
        # 英文按 .!? 拆分
        sentences = re.split(r'(?<=[.!?])\s+', text)
    return [s.strip() for s in sentences if s.strip()]

sentences = split_sentences(text, lang=lang)
for i, sentence in enumerate(sentences, 1):
    num = str(i).zfill(2)
    voice = 'zh-CN-XiaoxiaoNeural' if lang == 'zh' else 'en-US-EmmaNeural'
    subprocess.run([
        "uvx", "edge-tts",
        "-t", sentence,
        "-v", voice,
        "--rate=-10%",
        "--write-media", f"OUTPUT_DIR/sentence_{num}.mp3"
    ])

Output Directory

/mnt/d/wslspace/workspace/articles/YYYY-MM-DD-article-slug/
├── original_text.md
├── full_article.mp3
└── sentence_01.mp3 ...

Sending via Message Channel

The agent detects the active channel from the runtime context and calls `message(...)` accordingly. No hardcoded channel — the agent uses whichever channel the user is currently chatting through.

# Detect active channel automatically (from runtime inbound metadata)
# channel is inferred: feishu / telegram / discord / whatsapp / signal / imessage / openclaw-weixin

# 发送全文
message(action="send", channel="{active_channel}",
        message="📄 全文音频",
        media="PATH/full_article.mp3",
        filename="full_article.mp3")

# 发送每句
for i, sentence in enumerate(sentences, 1):
    num = str(i).zfill(2)
    message(action="send", channel="{active_channel}",
            message=f"📝 {num}: {sentence}",
            media=f"PATH/sentence_{num}.mp3",
            filename=f"sentence_{num}.mp3")

Channel Behavior Notes

| Channel | 音频支持 | 备注 |

|---------|---------|------|

| Feishu | ✅ | 直接发送 mp3 |

| Telegram | ✅ | 直接发送 mp3 |

| Discord | ✅ | 作为附件发送 |

| WhatsApp | ✅ | 直接发送 mp3 |

| Signal | ⚠️ | 取决于信号强度，可能不支持 |

| iMessage | ⚠️ | 通过 macOS 发送，mp3 兼容性一般 |

| WeChat Work | ✅ | 同 Feishu |

If the channel does not support audio, the agent saves the file to `OUTPUT_DIR` and sends the file path as a text message instead.

Available TTS Voices

English

`en-US-EmmaNeural`, `en-US-BrianNeural`, `en-GB-LibbyNeural`, ...

Chinese

`zh-CN-XiaoxiaoNeural`（女声）, `zh-CN-YunxiNeural`（男声）, `zh-CN-YunyangNeural`（新闻男声）, ...

查看完整列表：`uvx edge-tts -l | grep "zh-CN"`

Notes