videocut

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口播视频转录和口误识别。生成审查稿和删除任务清单。触发词:剪口播、处理视频、识别口误

Install

mkdir -p .claude/skills/videocut && curl -L -o skill.zip "https://mcp.directory/api/skills/download/5017" && unzip -o skill.zip -d .claude/skills/videocut && rm skill.zip

Installs to .claude/skills/videocut

About this skill

<!-- input: 视频文件 (*.mp4) output: subtitles_words.json、auto_selected.json、review.html pos: 转录+识别,到用户网页审核为止 架构守护者:一旦我被修改,请同步更新: 1. ../README.md 的 Skill 清单 2. /CLAUDE.md 路由表 -->

剪口播 v2

火山引擎转录 + AI 口误识别 + 网页审核

快速使用

用户: 帮我剪这个口播视频
用户: 处理一下这个视频

输出目录结构

output/
└── YYYY-MM-DD_视频名/
    ├── 剪口播/
    │   ├── 1_转录/
    │   │   ├── audio.mp3
    │   │   ├── volcengine_result.json
    │   │   └── subtitles_words.json
    │   ├── 2_分析/
    │   │   ├── readable.txt
    │   │   ├── auto_selected.json
    │   │   └── 口误分析.md
    │   └── 3_审核/
    │       └── review.html
    └── 字幕/
        └── ...

规则:已有文件夹则复用,否则新建。

流程

0. 创建输出目录
    ↓
1. 提取音频 (ffmpeg)
    ↓
2. 上传获取公网 URL (uguu.se)
    ↓
3. 火山引擎 API 转录
    ↓
4. 生成字级别字幕 (subtitles_words.json)
    ↓
5. AI 分析口误/静音,生成预选列表 (auto_selected.json)
    ↓
6. 生成审核网页 (review.html)
    ↓
7. 启动审核服务器,用户网页确认
    ↓
【等待用户确认】→ 网页点击「执行剪辑」或手动 /剪辑

执行步骤

步骤 0: 创建输出目录

# 变量设置(根据实际视频调整)
VIDEO_PATH="/path/to/视频.mp4"
VIDEO_NAME=$(basename "$VIDEO_PATH" .mp4)
DATE=$(date +%Y-%m-%d)
BASE_DIR="output/${DATE}_${VIDEO_NAME}/剪口播"

# 创建子目录
mkdir -p "$BASE_DIR/1_转录" "$BASE_DIR/2_分析" "$BASE_DIR/3_审核"
cd "$BASE_DIR"

步骤 1-3: 转录

cd 1_转录

# 1. 提取音频(文件名有冒号需加 file: 前缀)
ffmpeg -i "file:$VIDEO_PATH" -vn -acodec libmp3lame -y audio.mp3

# 2. 上传获取公网 URL
curl -s -F "files[]=@audio.mp3" https://uguu.se/upload
# 返回: {"success":true,"files":[{"url":"https://h.uguu.se/xxx.mp3"}]}

# 3. 调用火山引擎 API
SKILL_DIR="/Users/chengfeng/Desktop/AIos/剪辑Agent/.claude/skills/剪口播"
"$SKILL_DIR/scripts/volcengine_transcribe.sh" "https://h.uguu.se/xxx.mp3"
# 输出: volcengine_result.json

步骤 4: 生成字幕

node "$SKILL_DIR/scripts/generate_subtitles.js" volcengine_result.json
# 输出: subtitles_words.json

cd ..

步骤 5: 分析口误(脚本+AI)

5.1 生成易读格式

cd 2_分析

node -e "
const data = require('../1_转录/subtitles_words.json');
let output = [];
data.forEach((w, i) => {
  if (w.isGap) {
    const dur = (w.end - w.start).toFixed(2);
    if (dur >= 0.5) output.push(i + '|[静' + dur + 's]|' + w.start.toFixed(2) + '-' + w.end.toFixed(2));
  } else {
    output.push(i + '|' + w.text + '|' + w.start.toFixed(2) + '-' + w.end.toFixed(2));
  }
});
require('fs').writeFileSync('readable.txt', output.join('\\n'));
"

5.2 读取用户习惯

先读 用户习惯/ 目录下所有规则文件。

5.3 生成句子列表(关键步骤)

必须先分句,再分析。按静音切分成句子列表:

node -e "
const data = require('../1_转录/subtitles_words.json');
let sentences = [];
let curr = { text: '', startIdx: -1, endIdx: -1 };

data.forEach((w, i) => {
  const isLongGap = w.isGap && (w.end - w.start) >= 0.5;
  if (isLongGap) {
    if (curr.text.length > 0) sentences.push({...curr});
    curr = { text: '', startIdx: -1, endIdx: -1 };
  } else if (!w.isGap) {
    if (curr.startIdx === -1) curr.startIdx = i;
    curr.text += w.text;
    curr.endIdx = i;
  }
});
if (curr.text.length > 0) sentences.push(curr);

sentences.forEach((s, i) => {
  console.log(i + '|' + s.startIdx + '-' + s.endIdx + '|' + s.text);
});
" > sentences.txt

5.4 脚本自动标记静音(必须先执行)

node -e "
const words = require('../1_转录/subtitles_words.json');
const selected = [];
words.forEach((w, i) => {
  if (w.isGap && (w.end - w.start) >= 0.5) selected.push(i);
});
require('fs').writeFileSync('auto_selected.json', JSON.stringify(selected, null, 2));
console.log('≥0.5s静音数量:', selected.length);
"

→ 输出 auto_selected.json(只含静音 idx)

5.5 AI 分析口误(追加到 auto_selected.json)

检测规则(按优先级)

#类型判断方法删除范围
1重复句相邻句子开头≥5字相同较短的整句
2隔一句重复中间是残句时,比对前后句前句+残句
3残句话说一半+静音整个残句
4句内重复A+中间+A 模式前面部分
5卡顿词那个那个、就是就是前面部分
6重说纠正部分重复/否定纠正前面部分
7语气词嗯、啊、那个标记但不自动删

核心原则

  • 先分句,再比对:用 sentences.txt 比对相邻句子
  • 整句删除:残句、重复句都要删整句,不只是删异常的几个字

分段分析(循环执行)

1. Read readable.txt offset=N limit=300
2. 结合 sentences.txt 分析这300行
3. 追加口误 idx 到 auto_selected.json
4. 记录到 口误分析.md
5. N += 300,回到步骤1

🚨 关键警告:行号 ≠ idx

readable.txt 格式: idx|内容|时间
                   ↑ 用这个值

行号1500 → "1568|[静1.02s]|..."  ← idx是1568,不是1500!

口误分析.md 格式:

## 第N段 (行号范围)

| idx | 时间 | 类型 | 内容 | 处理 |
|-----|------|------|------|------|
| 65-75 | 15.80-17.66 | 重复句 | "这是我剪出来的一个案例" | 删 |

步骤 6-7: 审核

cd ../3_审核

# 6. 生成审核网页
node "$SKILL_DIR/scripts/generate_review.js" ../1_转录/subtitles_words.json ../2_分析/auto_selected.json ../1_转录/audio.mp3
# 输出: review.html

# 7. 启动审核服务器
node "$SKILL_DIR/scripts/review_server.js" 8899 "$VIDEO_PATH"
# 打开 http://localhost:8899

用户在网页中:

  • 播放视频片段确认
  • 勾选/取消删除项
  • 点击「执行剪辑」

数据格式

subtitles_words.json

[
  {"text": "大", "start": 0.12, "end": 0.2, "isGap": false},
  {"text": "", "start": 6.78, "end": 7.48, "isGap": true}
]

auto_selected.json

[72, 85, 120]  // Claude 分析生成的预选索引

配置

火山引擎 API Key

cd /Users/chengfeng/Desktop/AIos/剪辑Agent/.claude/skills
cp .env.example .env
# 编辑 .env 填入 VOLCENGINE_API_KEY=xxx

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